{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 人脸识别与计算机视觉文档实践\n",
    "\n",
    ">* 本周主要内容：人脸（Face） API文档不同平台对比与实践及计算机视觉入门（认知服务）\n",
    ">* 202009_API_人工智能与机器学习_week03\n",
    ">*  电子讲义设计者：许智超\n",
    "<br/>\n",
    "<br/>\n",
    "\n",
    "## 复习\n",
    "\n",
    "* 上周主要内容： \n",
    ">    * 1、API文档\n",
    ">    * 2、认知服务-人脸识别\n",
    ">    * 3、pandas黑魔法（json_normalize）\n",
    "-----\n",
    "* 提问、检查与扩展：\n",
    ">    * 1、上周的Azure face API随机检查2位同学，对于API文档是否有能力详细阅读？\n",
    ">    * 2、抽查2位同学，对于获取的数据用途有何思考？是否尝试其他平台（XXX API、XXX API）      \n",
    ">    * 3、扩展: 我们尝试抽取了4张图片，包含AB、ABC、BCD、ABCD四个人物特征，如何通过API检查数据差异？\n",
    "  \n",
    "\n",
    "-----\n",
    "## 本周学习目标：\n",
    "\n",
    "> $\\mathcal{1、Azure 认知服务-人脸集合演示}$     \n",
    "> $\\mathcal{2、Face++ 之 FaceSets 实践}$     \n",
    "> $\\mathcal{3、计算机视觉实践}$    \n",
    "\n",
    "\n",
    "\n",
    "## 学生权限\n",
    "\n",
    "* [访问学生权益](https://azure.microsoft.com/zh-cn/education/)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       "/* 本电子讲义使用之CSS */\n",
       "div.code_cell {\n",
       "    background-color: #e5f1fe;\n",
       "}\n",
       "div.cell.selected {\n",
       "    background-color: #effee2;\n",
       "    font-size: 2rem;\n",
       "    line-height: 2.4rem;\n",
       "}\n",
       "div.cell.selected .rendered_html table {\n",
       "    font-size: 2rem !important;\n",
       "    line-height: 2.4rem !important;\n",
       "}\n",
       ".rendered_html pre code {\n",
       "    background-color: #C4E4ff;   \n",
       "    padding: 2px 25px;\n",
       "}\n",
       ".rendered_html pre {\n",
       "    background-color: #99c9ff;\n",
       "}\n",
       "div.code_cell .CodeMirror {\n",
       "    font-size: 2rem !important;\n",
       "    line-height: 2.4rem !important;\n",
       "}\n",
       ".rendered_html img, .rendered_html svg {\n",
       "    max-width: 50%;\n",
       "    height: auto;\n",
       "    float: center;\n",
       "}\n",
       "/* Gradient transparent - color - transparent */\n",
       "hr {\n",
       "    border: 0;\n",
       "    border-bottom: 1px dashed #ccc;\n",
       "}\n",
       ".emoticon{\n",
       "    font-size: 5rem;\n",
       "    line-height: 4.4rem;\n",
       "    text-align: center;\n",
       "    vertical-align: middle;\n",
       "}\n",
       "\n",
       "</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%html\n",
    "<style>\n",
    "/* 本电子讲义使用之CSS */\n",
    "div.code_cell {\n",
    "    background-color: #e5f1fe;\n",
    "}\n",
    "div.cell.selected {\n",
    "    background-color: #effee2;\n",
    "    font-size: 2rem;\n",
    "    line-height: 2.4rem;\n",
    "}\n",
    "div.cell.selected .rendered_html table {\n",
    "    font-size: 2rem !important;\n",
    "    line-height: 2.4rem !important;\n",
    "}\n",
    ".rendered_html pre code {\n",
    "    background-color: #C4E4ff;   \n",
    "    padding: 2px 25px;\n",
    "}\n",
    ".rendered_html pre {\n",
    "    background-color: #99c9ff;\n",
    "}\n",
    "div.code_cell .CodeMirror {\n",
    "    font-size: 2rem !important;\n",
    "    line-height: 2.4rem !important;\n",
    "}\n",
    ".rendered_html img, .rendered_html svg {\n",
    "    max-width: 50%;\n",
    "    height: auto;\n",
    "    float: center;\n",
    "}\n",
    "/* Gradient transparent - color - transparent */\n",
    "hr {\n",
    "    border: 0;\n",
    "    border-bottom: 1px dashed #ccc;\n",
    "}\n",
    ".emoticon{\n",
    "    font-size: 5rem;\n",
    "    line-height: 4.4rem;\n",
    "    text-align: center;\n",
    "    vertical-align: middle;\n",
    "}\n",
    "\n",
    "</style>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 复习\n",
    "\n",
    "> 1、回顾阅读API文档的关键点     \n",
    "> 2、正确阅读json数据 [jsonviewer.stack.hu(json转换检查数据)](http://jsonviewer.stack.hu)    \n",
    "> 3、pandas 中的json_normalize模块/函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A-1 面部检测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'[{\"faceId\": \"14db2444-e70c-4297-9b88-c82bd75943ff\", \"faceRectangle\": {\"top\": 185, \"left\": 258, \"width\": 97, \"height\": 97}, \"faceAttributes\": {\"smile\": 0.022, \"headPose\": {\"pitch\": -9.5, \"roll\": 5.0, \"yaw\": -25.4}, \"gender\": \"female\", \"age\": 20.0, \"facialHair\": {\"moustache\": 0.0, \"beard\": 0.0, \"sideburns\": 0.0}, \"glasses\": \"NoGlasses\", \"emotion\": {\"anger\": 0.0, \"contempt\": 0.0, \"disgust\": 0.0, \"fear\": 0.0, \"happiness\": 0.022, \"neutral\": 0.977, \"sadness\": 0.001, \"surprise\": 0.0}, \"blur\": {\"blurLevel\": \"low\", \"value\": 0.05}, \"exposure\": {\"exposureLevel\": \"goodExposure\", \"value\": 0.65}, \"noise\": {\"noiseLevel\": \"low\", \"value\": 0.0}, \"makeup\": {\"eyeMakeup\": true, \"lipMakeup\": true}, \"accessories\": [], \"occlusion\": {\"foreheadOccluded\": false, \"eyeOccluded\": false, \"mouthOccluded\": false}, \"hair\": {\"bald\": 0.02, \"invisible\": false, \"hairColor\": [{\"color\": \"black\", \"confidence\": 1.0}, {\"color\": \"brown\", \"confidence\": 0.94}, {\"color\": \"gray\", \"confidence\": 0.29}, {\"color\": \"other\", \"confidence\": 0.25}, {\"color\": \"blond\", \"confidence\": 0.03}, {\"color\": \"red\", \"confidence\": 0.02}, {\"color\": \"white\", \"confidence\": 0.0}]}}}, {\"faceId\": \"ae357587-a895-4636-92cb-77e315fa0c1c\", \"faceRectangle\": {\"top\": 70, \"left\": 57, \"width\": 64, \"height\": 64}, \"faceAttributes\": {\"smile\": 1.0, \"headPose\": {\"pitch\": -9.1, \"roll\": 2.3, \"yaw\": 23.5}, \"gender\": \"male\", \"age\": 30.0, \"facialHair\": {\"moustache\": 0.1, \"beard\": 0.1, \"sideburns\": 0.1}, \"glasses\": \"NoGlasses\", \"emotion\": {\"anger\": 0.0, \"contempt\": 0.0, \"disgust\": 0.0, \"fear\": 0.0, \"happiness\": 1.0, \"neutral\": 0.0, \"sadness\": 0.0, \"surprise\": 0.0}, \"blur\": {\"blurLevel\": \"low\", \"value\": 0.02}, \"exposure\": {\"exposureLevel\": \"goodExposure\", \"value\": 0.66}, \"noise\": {\"noiseLevel\": \"low\", \"value\": 0.0}, \"makeup\": {\"eyeMakeup\": false, \"lipMakeup\": true}, \"accessories\": [], \"occlusion\": {\"foreheadOccluded\": false, \"eyeOccluded\": false, \"mouthOccluded\": false}, \"hair\": {\"bald\": 0.19, \"invisible\": false, \"hairColor\": [{\"color\": \"black\", \"confidence\": 1.0}, {\"color\": \"brown\", \"confidence\": 0.84}, {\"color\": \"other\", \"confidence\": 0.41}, {\"color\": \"gray\", \"confidence\": 0.3}, {\"color\": \"red\", \"confidence\": 0.02}, {\"color\": \"blond\", \"confidence\": 0.02}, {\"color\": \"white\", \"confidence\": 0.0}]}}}, {\"faceId\": \"92c47208-6790-4013-8af4-a77f3134015a\", \"faceRectangle\": {\"top\": 48, \"left\": 516, \"width\": 61, \"height\": 61}, \"faceAttributes\": {\"smile\": 1.0, \"headPose\": {\"pitch\": 0.3, \"roll\": -1.7, \"yaw\": -9.7}, \"gender\": \"male\", \"age\": 34.0, \"facialHair\": {\"moustache\": 0.1, \"beard\": 0.1, \"sideburns\": 0.1}, \"glasses\": \"NoGlasses\", \"emotion\": {\"anger\": 0.0, \"contempt\": 0.0, \"disgust\": 0.0, \"fear\": 0.0, \"happiness\": 1.0, \"neutral\": 0.0, \"sadness\": 0.0, \"surprise\": 0.0}, \"blur\": {\"blurLevel\": \"low\", \"value\": 0.11}, \"exposure\": {\"exposureLevel\": \"goodExposure\", \"value\": 0.71}, \"noise\": {\"noiseLevel\": \"low\", \"value\": 0.0}, \"makeup\": {\"eyeMakeup\": false, \"lipMakeup\": false}, \"accessories\": [], \"occlusion\": {\"foreheadOccluded\": false, \"eyeOccluded\": false, \"mouthOccluded\": false}, \"hair\": {\"bald\": 0.04, \"invisible\": false, \"hairColor\": [{\"color\": \"black\", \"confidence\": 0.99}, {\"color\": \"brown\", \"confidence\": 0.83}, {\"color\": \"gray\", \"confidence\": 0.39}, {\"color\": \"other\", \"confidence\": 0.37}, {\"color\": \"blond\", \"confidence\": 0.08}, {\"color\": \"red\", \"confidence\": 0.04}, {\"color\": \"white\", \"confidence\": 0.0}]}}}, {\"faceId\": \"3bb2478d-c7ef-4f65-bb61-f19694b31cbe\", \"faceRectangle\": {\"top\": 36, \"left\": 202, \"width\": 46, \"height\": 46}, \"faceAttributes\": {\"smile\": 1.0, \"headPose\": {\"pitch\": -0.7, \"roll\": -2.9, \"yaw\": -12.3}, \"gender\": \"male\", \"age\": 23.0, \"facialHair\": {\"moustache\": 0.1, \"beard\": 0.1, \"sideburns\": 0.1}, \"glasses\": \"NoGlasses\", \"emotion\": {\"anger\": 0.0, \"contempt\": 0.0, \"disgust\": 0.0, \"fear\": 0.0, \"happiness\": 1.0, \"neutral\": 0.0, \"sadness\": 0.0, \"surprise\": 0.0}, \"blur\": {\"blurLevel\": \"low\", \"value\": 0.12}, \"exposure\": {\"exposureLevel\": \"goodExposure\", \"value\": 0.56}, \"noise\": {\"noiseLevel\": \"low\", \"value\": 0.21}, \"makeup\": {\"eyeMakeup\": true, \"lipMakeup\": true}, \"accessories\": [], \"occlusion\": {\"foreheadOccluded\": false, \"eyeOccluded\": false, \"mouthOccluded\": false}, \"hair\": {\"bald\": 0.03, \"invisible\": false, \"hairColor\": [{\"color\": \"black\", \"confidence\": 1.0}, {\"color\": \"brown\", \"confidence\": 0.82}, {\"color\": \"other\", \"confidence\": 0.45}, {\"color\": \"gray\", \"confidence\": 0.31}, {\"color\": \"red\", \"confidence\": 0.02}, {\"color\": \"blond\", \"confidence\": 0.01}, {\"color\": \"white\", \"confidence\": 0.0}]}}}, {\"faceId\": \"eb6abbee-d233-41ee-a005-fc42f2ecb215\", \"faceRectangle\": {\"top\": 36, \"left\": 397, \"width\": 45, \"height\": 45}, \"faceAttributes\": {\"smile\": 0.0, \"headPose\": {\"pitch\": -0.7, \"roll\": 13.8, \"yaw\": -18.3}, \"gender\": \"male\", \"age\": 22.0, \"facialHair\": {\"moustache\": 0.1, \"beard\": 0.1, \"sideburns\": 0.1}, \"glasses\": \"NoGlasses\", \"emotion\": {\"anger\": 0.0, \"contempt\": 0.0, \"disgust\": 0.0, \"fear\": 0.0, \"happiness\": 0.0, \"neutral\": 0.998, \"sadness\": 0.002, \"surprise\": 0.0}, \"blur\": {\"blurLevel\": \"low\", \"value\": 0.0}, \"exposure\": {\"exposureLevel\": \"goodExposure\", \"value\": 0.53}, \"noise\": {\"noiseLevel\": \"low\", \"value\": 0.0}, \"makeup\": {\"eyeMakeup\": true, \"lipMakeup\": true}, \"accessories\": [], \"occlusion\": {\"foreheadOccluded\": false, \"eyeOccluded\": false, \"mouthOccluded\": false}, \"hair\": {\"bald\": 0.01, \"invisible\": false, \"hairColor\": [{\"color\": \"black\", \"confidence\": 1.0}, {\"color\": \"brown\", \"confidence\": 0.89}, {\"color\": \"gray\", \"confidence\": 0.59}, {\"color\": \"other\", \"confidence\": 0.33}, {\"color\": \"blond\", \"confidence\": 0.01}, {\"color\": \"red\", \"confidence\": 0.01}, {\"color\": \"white\", \"confidence\": 0.0}]}}}]'"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A-1 面部检测\n",
    "# 首先要调用requests,json\n",
    "import requests\n",
    "import json\n",
    "\n",
    "# set to your own subscription key value\n",
    "subscription_key = \"3948802e53ce4c44b8bfe0729a1d5def\" # 注册Azure后获取到的密钥\n",
    "assert subscription_key\n",
    "\n",
    "# replace <My Endpoint String> with the string from your endpoint URL\n",
    "face_api_url = 'https://api-linjm.cognitiveservices.azure.com/face/v1.0/detect' # 在Azure中API文档中获取的URL，其中{endpoint}用自己终结点的替代\n",
    "\n",
    "# 请求正文body\n",
    "image_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603472448023&di=52e19035ab7c8780e754ca69ec72ad8d&imgtype=0&src=http%3A%2F%2Fpics4.baidu.com%2Ffeed%2F32fa828ba61ea8d328c5b59b27bf0948271f5882.png%3Ftoken%3D853cc5bca56c55e1861e7817628d0275%26s%3D2BA36B850C1132D44DBD841D03006043\"\n",
    "# 填入想要检测的image_url(网上所搜的或本地的图片都可以)\n",
    "\n",
    "headers = {'Ocp-Apim-Subscription-Key': subscription_key}\n",
    "\n",
    "# 请求参数parameters\n",
    "params = {\n",
    "    'returnFaceId': 'true',\n",
    "    'returnFaceLandmarks': 'false',\n",
    "    # 可选参数,请仔细阅读API文档\n",
    "    'returnFaceAttributes': 'age,gender,headPose,smile,facialHair,glasses,emotion,hair,makeup,occlusion,accessories,blur,exposure,noise',\n",
    "}\n",
    "\n",
    "response = requests.post(face_api_url, params=params,\n",
    "                         headers=headers, json={\"url\": image_url})\n",
    "# json.dumps 将json--->bytes\n",
    "json.dumps(response.json())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A-2 json转译\n",
    "\n",
    "> * bytes ---> json\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'faceId': '14db2444-e70c-4297-9b88-c82bd75943ff',\n",
       "  'faceRectangle': {'top': 185, 'left': 258, 'width': 97, 'height': 97},\n",
       "  'faceAttributes': {'smile': 0.022,\n",
       "   'headPose': {'pitch': -9.5, 'roll': 5.0, 'yaw': -25.4},\n",
       "   'gender': 'female',\n",
       "   'age': 20.0,\n",
       "   'facialHair': {'moustache': 0.0, 'beard': 0.0, 'sideburns': 0.0},\n",
       "   'glasses': 'NoGlasses',\n",
       "   'emotion': {'anger': 0.0,\n",
       "    'contempt': 0.0,\n",
       "    'disgust': 0.0,\n",
       "    'fear': 0.0,\n",
       "    'happiness': 0.022,\n",
       "    'neutral': 0.977,\n",
       "    'sadness': 0.001,\n",
       "    'surprise': 0.0},\n",
       "   'blur': {'blurLevel': 'low', 'value': 0.05},\n",
       "   'exposure': {'exposureLevel': 'goodExposure', 'value': 0.65},\n",
       "   'noise': {'noiseLevel': 'low', 'value': 0.0},\n",
       "   'makeup': {'eyeMakeup': True, 'lipMakeup': True},\n",
       "   'accessories': [],\n",
       "   'occlusion': {'foreheadOccluded': False,\n",
       "    'eyeOccluded': False,\n",
       "    'mouthOccluded': False},\n",
       "   'hair': {'bald': 0.02,\n",
       "    'invisible': False,\n",
       "    'hairColor': [{'color': 'black', 'confidence': 1.0},\n",
       "     {'color': 'brown', 'confidence': 0.94},\n",
       "     {'color': 'gray', 'confidence': 0.29},\n",
       "     {'color': 'other', 'confidence': 0.25},\n",
       "     {'color': 'blond', 'confidence': 0.03},\n",
       "     {'color': 'red', 'confidence': 0.02},\n",
       "     {'color': 'white', 'confidence': 0.0}]}}},\n",
       " {'faceId': 'ae357587-a895-4636-92cb-77e315fa0c1c',\n",
       "  'faceRectangle': {'top': 70, 'left': 57, 'width': 64, 'height': 64},\n",
       "  'faceAttributes': {'smile': 1.0,\n",
       "   'headPose': {'pitch': -9.1, 'roll': 2.3, 'yaw': 23.5},\n",
       "   'gender': 'male',\n",
       "   'age': 30.0,\n",
       "   'facialHair': {'moustache': 0.1, 'beard': 0.1, 'sideburns': 0.1},\n",
       "   'glasses': 'NoGlasses',\n",
       "   'emotion': {'anger': 0.0,\n",
       "    'contempt': 0.0,\n",
       "    'disgust': 0.0,\n",
       "    'fear': 0.0,\n",
       "    'happiness': 1.0,\n",
       "    'neutral': 0.0,\n",
       "    'sadness': 0.0,\n",
       "    'surprise': 0.0},\n",
       "   'blur': {'blurLevel': 'low', 'value': 0.02},\n",
       "   'exposure': {'exposureLevel': 'goodExposure', 'value': 0.66},\n",
       "   'noise': {'noiseLevel': 'low', 'value': 0.0},\n",
       "   'makeup': {'eyeMakeup': False, 'lipMakeup': True},\n",
       "   'accessories': [],\n",
       "   'occlusion': {'foreheadOccluded': False,\n",
       "    'eyeOccluded': False,\n",
       "    'mouthOccluded': False},\n",
       "   'hair': {'bald': 0.19,\n",
       "    'invisible': False,\n",
       "    'hairColor': [{'color': 'black', 'confidence': 1.0},\n",
       "     {'color': 'brown', 'confidence': 0.84},\n",
       "     {'color': 'other', 'confidence': 0.41},\n",
       "     {'color': 'gray', 'confidence': 0.3},\n",
       "     {'color': 'red', 'confidence': 0.02},\n",
       "     {'color': 'blond', 'confidence': 0.02},\n",
       "     {'color': 'white', 'confidence': 0.0}]}}},\n",
       " {'faceId': '92c47208-6790-4013-8af4-a77f3134015a',\n",
       "  'faceRectangle': {'top': 48, 'left': 516, 'width': 61, 'height': 61},\n",
       "  'faceAttributes': {'smile': 1.0,\n",
       "   'headPose': {'pitch': 0.3, 'roll': -1.7, 'yaw': -9.7},\n",
       "   'gender': 'male',\n",
       "   'age': 34.0,\n",
       "   'facialHair': {'moustache': 0.1, 'beard': 0.1, 'sideburns': 0.1},\n",
       "   'glasses': 'NoGlasses',\n",
       "   'emotion': {'anger': 0.0,\n",
       "    'contempt': 0.0,\n",
       "    'disgust': 0.0,\n",
       "    'fear': 0.0,\n",
       "    'happiness': 1.0,\n",
       "    'neutral': 0.0,\n",
       "    'sadness': 0.0,\n",
       "    'surprise': 0.0},\n",
       "   'blur': {'blurLevel': 'low', 'value': 0.11},\n",
       "   'exposure': {'exposureLevel': 'goodExposure', 'value': 0.71},\n",
       "   'noise': {'noiseLevel': 'low', 'value': 0.0},\n",
       "   'makeup': {'eyeMakeup': False, 'lipMakeup': False},\n",
       "   'accessories': [],\n",
       "   'occlusion': {'foreheadOccluded': False,\n",
       "    'eyeOccluded': False,\n",
       "    'mouthOccluded': False},\n",
       "   'hair': {'bald': 0.04,\n",
       "    'invisible': False,\n",
       "    'hairColor': [{'color': 'black', 'confidence': 0.99},\n",
       "     {'color': 'brown', 'confidence': 0.83},\n",
       "     {'color': 'gray', 'confidence': 0.39},\n",
       "     {'color': 'other', 'confidence': 0.37},\n",
       "     {'color': 'blond', 'confidence': 0.08},\n",
       "     {'color': 'red', 'confidence': 0.04},\n",
       "     {'color': 'white', 'confidence': 0.0}]}}},\n",
       " {'faceId': '3bb2478d-c7ef-4f65-bb61-f19694b31cbe',\n",
       "  'faceRectangle': {'top': 36, 'left': 202, 'width': 46, 'height': 46},\n",
       "  'faceAttributes': {'smile': 1.0,\n",
       "   'headPose': {'pitch': -0.7, 'roll': -2.9, 'yaw': -12.3},\n",
       "   'gender': 'male',\n",
       "   'age': 23.0,\n",
       "   'facialHair': {'moustache': 0.1, 'beard': 0.1, 'sideburns': 0.1},\n",
       "   'glasses': 'NoGlasses',\n",
       "   'emotion': {'anger': 0.0,\n",
       "    'contempt': 0.0,\n",
       "    'disgust': 0.0,\n",
       "    'fear': 0.0,\n",
       "    'happiness': 1.0,\n",
       "    'neutral': 0.0,\n",
       "    'sadness': 0.0,\n",
       "    'surprise': 0.0},\n",
       "   'blur': {'blurLevel': 'low', 'value': 0.12},\n",
       "   'exposure': {'exposureLevel': 'goodExposure', 'value': 0.56},\n",
       "   'noise': {'noiseLevel': 'low', 'value': 0.21},\n",
       "   'makeup': {'eyeMakeup': True, 'lipMakeup': True},\n",
       "   'accessories': [],\n",
       "   'occlusion': {'foreheadOccluded': False,\n",
       "    'eyeOccluded': False,\n",
       "    'mouthOccluded': False},\n",
       "   'hair': {'bald': 0.03,\n",
       "    'invisible': False,\n",
       "    'hairColor': [{'color': 'black', 'confidence': 1.0},\n",
       "     {'color': 'brown', 'confidence': 0.82},\n",
       "     {'color': 'other', 'confidence': 0.45},\n",
       "     {'color': 'gray', 'confidence': 0.31},\n",
       "     {'color': 'red', 'confidence': 0.02},\n",
       "     {'color': 'blond', 'confidence': 0.01},\n",
       "     {'color': 'white', 'confidence': 0.0}]}}},\n",
       " {'faceId': 'eb6abbee-d233-41ee-a005-fc42f2ecb215',\n",
       "  'faceRectangle': {'top': 36, 'left': 397, 'width': 45, 'height': 45},\n",
       "  'faceAttributes': {'smile': 0.0,\n",
       "   'headPose': {'pitch': -0.7, 'roll': 13.8, 'yaw': -18.3},\n",
       "   'gender': 'male',\n",
       "   'age': 22.0,\n",
       "   'facialHair': {'moustache': 0.1, 'beard': 0.1, 'sideburns': 0.1},\n",
       "   'glasses': 'NoGlasses',\n",
       "   'emotion': {'anger': 0.0,\n",
       "    'contempt': 0.0,\n",
       "    'disgust': 0.0,\n",
       "    'fear': 0.0,\n",
       "    'happiness': 0.0,\n",
       "    'neutral': 0.998,\n",
       "    'sadness': 0.002,\n",
       "    'surprise': 0.0},\n",
       "   'blur': {'blurLevel': 'low', 'value': 0.0},\n",
       "   'exposure': {'exposureLevel': 'goodExposure', 'value': 0.53},\n",
       "   'noise': {'noiseLevel': 'low', 'value': 0.0},\n",
       "   'makeup': {'eyeMakeup': True, 'lipMakeup': True},\n",
       "   'accessories': [],\n",
       "   'occlusion': {'foreheadOccluded': False,\n",
       "    'eyeOccluded': False,\n",
       "    'mouthOccluded': False},\n",
       "   'hair': {'bald': 0.01,\n",
       "    'invisible': False,\n",
       "    'hairColor': [{'color': 'black', 'confidence': 1.0},\n",
       "     {'color': 'brown', 'confidence': 0.89},\n",
       "     {'color': 'gray', 'confidence': 0.59},\n",
       "     {'color': 'other', 'confidence': 0.33},\n",
       "     {'color': 'blond', 'confidence': 0.01},\n",
       "     {'color': 'red', 'confidence': 0.01},\n",
       "     {'color': 'white', 'confidence': 0.0}]}}}]"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A-2\n",
    "results = response.json()\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A-3 pandas 数据表格化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>faceId</th>\n",
       "      <th>faceRectangle.top</th>\n",
       "      <th>faceRectangle.left</th>\n",
       "      <th>faceRectangle.width</th>\n",
       "      <th>faceRectangle.height</th>\n",
       "      <th>faceAttributes.smile</th>\n",
       "      <th>faceAttributes.headPose.pitch</th>\n",
       "      <th>faceAttributes.headPose.roll</th>\n",
       "      <th>faceAttributes.headPose.yaw</th>\n",
       "      <th>faceAttributes.gender</th>\n",
       "      <th>...</th>\n",
       "      <th>faceAttributes.noise.value</th>\n",
       "      <th>faceAttributes.makeup.eyeMakeup</th>\n",
       "      <th>faceAttributes.makeup.lipMakeup</th>\n",
       "      <th>faceAttributes.accessories</th>\n",
       "      <th>faceAttributes.occlusion.foreheadOccluded</th>\n",
       "      <th>faceAttributes.occlusion.eyeOccluded</th>\n",
       "      <th>faceAttributes.occlusion.mouthOccluded</th>\n",
       "      <th>faceAttributes.hair.bald</th>\n",
       "      <th>faceAttributes.hair.invisible</th>\n",
       "      <th>faceAttributes.hair.hairColor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14db2444-e70c-4297-9b88-c82bd75943ff</td>\n",
       "      <td>185</td>\n",
       "      <td>258</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>0.022</td>\n",
       "      <td>-9.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-25.4</td>\n",
       "      <td>female</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>[]</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.02</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'color': 'black', 'confidence': 1.0}, {'colo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ae357587-a895-4636-92cb-77e315fa0c1c</td>\n",
       "      <td>70</td>\n",
       "      <td>57</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>1.000</td>\n",
       "      <td>-9.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>23.5</td>\n",
       "      <td>male</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>[]</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.19</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'color': 'black', 'confidence': 1.0}, {'colo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>92c47208-6790-4013-8af4-a77f3134015a</td>\n",
       "      <td>48</td>\n",
       "      <td>516</td>\n",
       "      <td>61</td>\n",
       "      <td>61</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.3</td>\n",
       "      <td>-1.7</td>\n",
       "      <td>-9.7</td>\n",
       "      <td>male</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>[]</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.04</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'color': 'black', 'confidence': 0.99}, {'col...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3bb2478d-c7ef-4f65-bb61-f19694b31cbe</td>\n",
       "      <td>36</td>\n",
       "      <td>202</td>\n",
       "      <td>46</td>\n",
       "      <td>46</td>\n",
       "      <td>1.000</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>-2.9</td>\n",
       "      <td>-12.3</td>\n",
       "      <td>male</td>\n",
       "      <td>...</td>\n",
       "      <td>0.21</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>[]</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.03</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'color': 'black', 'confidence': 1.0}, {'colo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>eb6abbee-d233-41ee-a005-fc42f2ecb215</td>\n",
       "      <td>36</td>\n",
       "      <td>397</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>13.8</td>\n",
       "      <td>-18.3</td>\n",
       "      <td>male</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>[]</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.01</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'color': 'black', 'confidence': 1.0}, {'colo...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 faceId  faceRectangle.top  \\\n",
       "0  14db2444-e70c-4297-9b88-c82bd75943ff                185   \n",
       "1  ae357587-a895-4636-92cb-77e315fa0c1c                 70   \n",
       "2  92c47208-6790-4013-8af4-a77f3134015a                 48   \n",
       "3  3bb2478d-c7ef-4f65-bb61-f19694b31cbe                 36   \n",
       "4  eb6abbee-d233-41ee-a005-fc42f2ecb215                 36   \n",
       "\n",
       "   faceRectangle.left  faceRectangle.width  faceRectangle.height  \\\n",
       "0                 258                   97                    97   \n",
       "1                  57                   64                    64   \n",
       "2                 516                   61                    61   \n",
       "3                 202                   46                    46   \n",
       "4                 397                   45                    45   \n",
       "\n",
       "   faceAttributes.smile  faceAttributes.headPose.pitch  \\\n",
       "0                 0.022                           -9.5   \n",
       "1                 1.000                           -9.1   \n",
       "2                 1.000                            0.3   \n",
       "3                 1.000                           -0.7   \n",
       "4                 0.000                           -0.7   \n",
       "\n",
       "   faceAttributes.headPose.roll  faceAttributes.headPose.yaw  \\\n",
       "0                           5.0                        -25.4   \n",
       "1                           2.3                         23.5   \n",
       "2                          -1.7                         -9.7   \n",
       "3                          -2.9                        -12.3   \n",
       "4                          13.8                        -18.3   \n",
       "\n",
       "  faceAttributes.gender  ...  faceAttributes.noise.value  \\\n",
       "0                female  ...                        0.00   \n",
       "1                  male  ...                        0.00   \n",
       "2                  male  ...                        0.00   \n",
       "3                  male  ...                        0.21   \n",
       "4                  male  ...                        0.00   \n",
       "\n",
       "   faceAttributes.makeup.eyeMakeup  faceAttributes.makeup.lipMakeup  \\\n",
       "0                             True                             True   \n",
       "1                            False                             True   \n",
       "2                            False                            False   \n",
       "3                             True                             True   \n",
       "4                             True                             True   \n",
       "\n",
       "   faceAttributes.accessories faceAttributes.occlusion.foreheadOccluded  \\\n",
       "0                          []                                     False   \n",
       "1                          []                                     False   \n",
       "2                          []                                     False   \n",
       "3                          []                                     False   \n",
       "4                          []                                     False   \n",
       "\n",
       "   faceAttributes.occlusion.eyeOccluded  \\\n",
       "0                                 False   \n",
       "1                                 False   \n",
       "2                                 False   \n",
       "3                                 False   \n",
       "4                                 False   \n",
       "\n",
       "   faceAttributes.occlusion.mouthOccluded  faceAttributes.hair.bald  \\\n",
       "0                                   False                      0.02   \n",
       "1                                   False                      0.19   \n",
       "2                                   False                      0.04   \n",
       "3                                   False                      0.03   \n",
       "4                                   False                      0.01   \n",
       "\n",
       "   faceAttributes.hair.invisible  \\\n",
       "0                          False   \n",
       "1                          False   \n",
       "2                          False   \n",
       "3                          False   \n",
       "4                          False   \n",
       "\n",
       "                       faceAttributes.hair.hairColor  \n",
       "0  [{'color': 'black', 'confidence': 1.0}, {'colo...  \n",
       "1  [{'color': 'black', 'confidence': 1.0}, {'colo...  \n",
       "2  [{'color': 'black', 'confidence': 0.99}, {'col...  \n",
       "3  [{'color': 'black', 'confidence': 1.0}, {'colo...  \n",
       "4  [{'color': 'black', 'confidence': 1.0}, {'colo...  \n",
       "\n",
       "[5 rows x 38 columns]"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A-3\n",
    "import pandas as pd\n",
    "df_face = pd.json_normalize(results)\n",
    "df_face"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A-4 数据取值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['14db2444-e70c-4297-9b88-c82bd75943ff',\n",
       " 'ae357587-a895-4636-92cb-77e315fa0c1c',\n",
       " '92c47208-6790-4013-8af4-a77f3134015a',\n",
       " '3bb2478d-c7ef-4f65-bb61-f19694b31cbe',\n",
       " 'eb6abbee-d233-41ee-a005-fc42f2ecb215']"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "faceID = df_face['faceId'].values.tolist()\n",
    "faceID "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['faceId', 'faceRectangle.top', 'faceRectangle.left',\n",
       "       'faceRectangle.width', 'faceRectangle.height', 'faceAttributes.smile',\n",
       "       'faceAttributes.headPose.pitch', 'faceAttributes.headPose.roll',\n",
       "       'faceAttributes.headPose.yaw', 'faceAttributes.gender',\n",
       "       'faceAttributes.age', 'faceAttributes.facialHair.moustache',\n",
       "       'faceAttributes.facialHair.beard',\n",
       "       'faceAttributes.facialHair.sideburns', 'faceAttributes.glasses',\n",
       "       'faceAttributes.emotion.anger', 'faceAttributes.emotion.contempt',\n",
       "       'faceAttributes.emotion.disgust', 'faceAttributes.emotion.fear',\n",
       "       'faceAttributes.emotion.happiness', 'faceAttributes.emotion.neutral',\n",
       "       'faceAttributes.emotion.sadness', 'faceAttributes.emotion.surprise',\n",
       "       'faceAttributes.blur.blurLevel', 'faceAttributes.blur.value',\n",
       "       'faceAttributes.exposure.exposureLevel',\n",
       "       'faceAttributes.exposure.value', 'faceAttributes.noise.noiseLevel',\n",
       "       'faceAttributes.noise.value', 'faceAttributes.makeup.eyeMakeup',\n",
       "       'faceAttributes.makeup.lipMakeup', 'faceAttributes.accessories',\n",
       "       'faceAttributes.occlusion.foreheadOccluded',\n",
       "       'faceAttributes.occlusion.eyeOccluded',\n",
       "       'faceAttributes.occlusion.mouthOccluded', 'faceAttributes.hair.bald',\n",
       "       'faceAttributes.hair.invisible', 'faceAttributes.hair.hairColor'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 检查属性/特征值\n",
    "df_face.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>faceId</th>\n",
       "      <th>faceAttributes.glasses</th>\n",
       "      <th>faceAttributes.emotion.neutral</th>\n",
       "      <th>faceAttributes.age</th>\n",
       "      <th>faceAttributes.gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1f2bf379-70dd-41be-86c3-a63f2deb7c7f</td>\n",
       "      <td>NoGlasses</td>\n",
       "      <td>0.184</td>\n",
       "      <td>19.0</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>f659ea05-a658-497d-9b2a-eb89e74d5403</td>\n",
       "      <td>NoGlasses</td>\n",
       "      <td>0.542</td>\n",
       "      <td>22.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5e17a0f5-0a18-4a83-821a-31dd3fd014cd</td>\n",
       "      <td>ReadingGlasses</td>\n",
       "      <td>0.000</td>\n",
       "      <td>25.0</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c9b6de20-4b5c-4a87-88ce-482b2049a45c</td>\n",
       "      <td>NoGlasses</td>\n",
       "      <td>0.000</td>\n",
       "      <td>23.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c29e7a06-72de-4b77-bc5d-5568145f10eb</td>\n",
       "      <td>ReadingGlasses</td>\n",
       "      <td>0.019</td>\n",
       "      <td>18.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0192c19c-eb0a-447b-82f1-740f32eb004a</td>\n",
       "      <td>NoGlasses</td>\n",
       "      <td>0.000</td>\n",
       "      <td>19.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 faceId faceAttributes.glasses  \\\n",
       "0  1f2bf379-70dd-41be-86c3-a63f2deb7c7f              NoGlasses   \n",
       "1  f659ea05-a658-497d-9b2a-eb89e74d5403              NoGlasses   \n",
       "2  5e17a0f5-0a18-4a83-821a-31dd3fd014cd         ReadingGlasses   \n",
       "3  c9b6de20-4b5c-4a87-88ce-482b2049a45c              NoGlasses   \n",
       "4  c29e7a06-72de-4b77-bc5d-5568145f10eb         ReadingGlasses   \n",
       "5  0192c19c-eb0a-447b-82f1-740f32eb004a              NoGlasses   \n",
       "\n",
       "   faceAttributes.emotion.neutral  faceAttributes.age faceAttributes.gender  \n",
       "0                           0.184                19.0                  male  \n",
       "1                           0.542                22.0                female  \n",
       "2                           0.000                25.0                  male  \n",
       "3                           0.000                23.0                female  \n",
       "4                           0.019                18.0                female  \n",
       "5                           0.000                19.0                female  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 可观察其中几组数据\n",
    "df_face[['faceId','faceAttributes.glasses','faceAttributes.emotion.neutral','faceAttributes.age','faceAttributes.gender']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Azure 认知服务-人脸演示"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 试一试：人脸验证(难)\n",
    "\n",
    "人脸相似度？有没有试下？\n",
    "\n",
    ">* API人脸文档中最重要的组成部分：\n",
    " >>* Request URL？\n",
    " >>* Http Method？\n",
    " >>* 参数？\n",
    "\n",
    "----\n",
    ">* 不同的人脸对比数据\n",
    "  >>* 人脸验证关键数据？\n",
    "  >>* 根据哪些数据证明是同一个人？\n",
    "    \n",
    "----\n",
    ">* 具体步骤：\n",
    "  >>* 1、Create 请求成功200 返回空字符串\n",
    "  >>* 2、Add face 请求成功200 返回persistedFaceId\n",
    "  >>* 3、Detect 准备 被检测人 人脸的id\n",
    "  >>* 4、Find similars 返回相似置信度\n",
    "  >>* 附加：get查看facelists\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://api-hjq.cognitiveservices.azure.com/face/v1.0/facelists/zhichao02 \n",
      " https://api-hjq.cognitiveservices.azure.com/face/v1.0/facelists/zhichao02 \n",
      " https://api-hjq.cognitiveservices.azure.com/face/v1.0/facelists/zhichao02\n"
     ]
    }
   ],
   "source": [
    "# 字符串拼接练习\n",
    "faceListId = \"zhichao02\"\n",
    "# 1 +\n",
    "url_01 = \"https://api-hjq.cognitiveservices.azure.com/face/v1.0/facelists/\" + faceListId # string 拼接\n",
    "# 2 %s(占位符，有顺序)\n",
    "url_02 = \"https://api-hjq.cognitiveservices.azure.com/face/v1.0/facelists/%s\" %(faceListId)\n",
    "# 3 format\n",
    "url_03 = \"https://api-hjq.cognitiveservices.azure.com/face/v1.0/facelists/{}\".format(faceListId)\n",
    "print(url_01,'\\n',url_02,'\\n',url_03)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### create facelist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "# 1、create  list列表\n",
    "# faceListId\n",
    "faceListId =  \"linjm1218\" # 是唯一的，自定义填写，但要注意格式，具体格式可在API文档中看到，\n",
    "create_facelists_url = \"https://api-linjm.cognitiveservices.azure.com/face/v1.0/facelists/linjm1218\" # 可在API文档中获取此URL，其中的{endpoint}和{faceListID}要填写自己的\n",
    "subscription_key = \"3948802e53ce4c44b8bfe0729a1d5def\" # 可在Azure中的密钥中获取\n",
    "assert subscription_key\n",
    "\n",
    "headers = {\n",
    "    # Request headers\n",
    "    'Content-Type': 'application/json',\n",
    "    'Ocp-Apim-Subscription-Key': subscription_key,\n",
    "}\n",
    "data = {\n",
    "    \"name\": \"以家人之名\",\n",
    "    \"userData\": \"以家人之名一家人\",\n",
    "    \"recognitionModel\": \"recognition_03\",\n",
    "    \n",
    "}\n",
    "\n",
    "r_create = requests.put(create_facelists_url,headers=headers,json=data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_create"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b''"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_create.content"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### get facelist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 检查你的facelist的信息\n",
    "get_facelist_url = \"https://api-linjm.cognitiveservices.azure.com/face/v1.0/facelists/linjm1218\" # 与上面的create_facelists_url 一样\n",
    "r_get_facelist = requests.get(get_facelist_url,headers=headers)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'persistedFaces': [],\n",
       " 'faceListId': 'linjm1218',\n",
       " 'name': '以家人之名',\n",
       " 'userData': '以家人之名一家人'}"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_get_facelist.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add face 请求成功200 返回persistedFaceId\n",
    "> 我们通过上面的步骤建好了一个脸的列表，接下来我们要给这个列表添加脸了！把我们想要对比的脸存进列表吧\n",
    "- [添加人脸进列表api文档](https://docs.microsoft.com/zh-cn/rest/api/cognitiveservices/face/facelist/addfacefromurl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "#先加一张脸试试\n",
    "# 2、Add face\n",
    "add_face_url = \"https://api-linjm.cognitiveservices.azure.com/face/v1.0/facelists/linjm1218/persistedfaces\" #\n",
    "\n",
    "assert subscription_key\n",
    "headers = {\n",
    "    # Request headers\n",
    "    'Content-Type': 'application/json',\n",
    "    'Ocp-Apim-Subscription-Key': subscription_key,\n",
    "}\n",
    "img_url =  'https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603547249308&di=c000f778b4fe517140a9b7e4a6c950ef&imgtype=0&src=http%3A%2F%2Fn.sinaimg.cn%2Fsinakd20200314ac%2F620%2Fw640h780%2F20200314%2F6a0a-iquxrui2306103.jpg'\n",
    "params_add_face={\n",
    "    \"userData\":\"tansongyun\"\n",
    "}\n",
    "\n",
    "r_add_face = requests.post(add_face_url,headers=headers,params=params_add_face,json={\"url\":img_url})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_add_face.status_code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'persistedFaceId': 'cba421f9-6ba4-4651-843d-f772f5b9c048'}"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_add_face.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'persistedFaces': [{'persistedFaceId': '2ceb3433-34b0-4ea0-9903-7e54075a6ad3',\n",
       "   'userData': '黄杰琪师兄'},\n",
       "  {'persistedFaceId': 'd7e3eef0-742a-40ce-b71d-4cce6e786b9a',\n",
       "   'userData': 'tansongyun'},\n",
       "  {'persistedFaceId': 'cba421f9-6ba4-4651-843d-f772f5b9c048',\n",
       "   'userData': 'tansongyun'}],\n",
       " 'faceListId': 'linjm1218',\n",
       " 'name': '以家人之名',\n",
       " 'userData': '以家人之名一家人'}"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 检查你的facelist的信息\n",
    "get_facelist_url =  \"https://api-linjm.cognitiveservices.azure.com/face/v1.0/facelists/linjm1218\"\n",
    "r_get_facelist = requests.get(get_facelist_url,headers=headers)\n",
    "r_get_facelist.json()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 扩展内容，封装成函数方便多次使用 *\n",
    "> 我们要添加多张脸，但是为了减少代码量，我们可以把代码封装成函数，避免每次都要写一大堆代码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 封装成函数方便添加图片/函数——可以重复使用相同的功能\n",
    "def AddFace(img_url=str,userData=str):\n",
    "    add_face_url =\"https://api-linjm.cognitiveservices.azure.com/face/v1.0/facelists/{}/persistedFaces\"\n",
    "    assert subscription_key\n",
    "    headers = {\n",
    "        # Request headers\n",
    "        'Content-Type': 'application/json',\n",
    "        'Ocp-Apim-Subscription-Key': subscription_key,\n",
    "    }\n",
    "    img_url = img_url\n",
    "\n",
    "    params_add_face={\n",
    "        \"userData\":userData\n",
    "    }\n",
    "    r_add_face = requests.post(add_face_url.format(faceListId),headers=headers,params=params_add_face,json={\"url\":img_url})\n",
    "    return r_add_face.status_code#返回出状态码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "429"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/Autumnhui.jpg\",\"丘天惠\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/L-Tony-info.jpg\",\"林嘉茵\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/TLINGP.jpg\",\"汤玲萍\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/WenYanZeng.jpg\",\"曾雯燕\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/XIEIC.jpg\",\"谢依希\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/YuecongYang.png\",\"杨悦聪\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/Zoezhouyu.jpg\",\"周雨\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/crayon-heimi.jpg\",\"刘瑜鹏\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/jiayichen.jpg\",\"陈嘉仪\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/kg2000.jpg\",\"徐旖芊\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/liuxinrujiayou.jpg\",\"刘心如\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/liuyu19.png\",\"刘宇\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/ltco.jpg\",\"李婷\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/lucaszy.jpg\",\"黄智毅\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/pingzi0211.jpg\",\"黄慧文\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/shmimy-cn.jpg\",\"张铭睿\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/yichenting.jpg\",\"陈婷\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/coco022.jpg\",\"洪可凡\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/lujizhi.png\",\"卢继志\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/zzlhyy.jpg\",\"张梓乐\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'error': {'code': '429',\n",
       "  'message': 'Requests to the FaceList - Get Operation under Face API - v1.0 have exceeded rate limit of your current Face F0 pricing tier. Please retry after 9 seconds. To increase your rate limit switch to a paid tier.'}}"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 检查你的facelist的信息\n",
    "get_facelist_url = \"https://api-linjm.cognitiveservices.azure.com/face/v1.0/facelists/linjm1218\"\n",
    "r_get_facelist = requests.get(get_facelist_url,headers=headers)\n",
    "r_get_facelist.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'3b612f0c-b09e-4a5b-a2dc-0e0ec9e766e3'"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 键/值\n",
    "for i in faceId:\n",
    "#     print(i)\n",
    "    if i[\"userData\"] == \"周雨\":\n",
    "        faceId_02 = i['persistedFaceId']\n",
    "faceId_02\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'persistedFaceId': '39d84ebc-c8ea-4a0c-b714-23d7496529a9',\n",
       "  'userData': '丘天惠'},\n",
       " {'persistedFaceId': '79d4fae2-4e19-4ff7-83fa-0b3bdeddc6de',\n",
       "  'userData': '林嘉茵'},\n",
       " {'persistedFaceId': 'ecc62b78-a2bc-430c-8858-73c0a8af6225',\n",
       "  'userData': '汤玲萍'},\n",
       " {'persistedFaceId': 'ea43d732-b4fb-4b63-aba4-8ac36668a90d',\n",
       "  'userData': '曾雯燕'},\n",
       " {'persistedFaceId': '620cf149-1192-4b83-81e9-218d3b6c0d59',\n",
       "  'userData': '谢依希'},\n",
       " {'persistedFaceId': 'f043baf1-9685-43d0-8892-af1c706daea9',\n",
       "  'userData': '杨悦聪'},\n",
       " {'persistedFaceId': '3b612f0c-b09e-4a5b-a2dc-0e0ec9e766e3', 'userData': '周雨'},\n",
       " {'persistedFaceId': 'cf94a503-2af2-4fd0-9c36-8e1c14a4d4ca',\n",
       "  'userData': '刘瑜鹏'},\n",
       " {'persistedFaceId': '3a89cc86-4498-4f48-8fb3-159e9a703f4b',\n",
       "  'userData': '陈嘉仪'},\n",
       " {'persistedFaceId': '2ba84b46-db53-4173-992a-6a951b9c3cbe',\n",
       "  'userData': '徐旖芊'},\n",
       " {'persistedFaceId': 'bc8894a6-11f9-4a15-8fb4-49b2529d6ced',\n",
       "  'userData': '刘心如'},\n",
       " {'persistedFaceId': 'f958b4ed-f2fb-452f-b96b-5a526d33cd98', 'userData': '刘宇'},\n",
       " {'persistedFaceId': '84b74027-bd6b-4056-9a4b-5b32eb45301f', 'userData': '李婷'},\n",
       " {'persistedFaceId': '271b2adc-23b9-4f54-a54a-0388a0da90dd',\n",
       "  'userData': '黄智毅'},\n",
       " {'persistedFaceId': '66a5fb8b-1d80-4d85-9f4c-168858072eb2',\n",
       "  'userData': '黄慧文'},\n",
       " {'persistedFaceId': '0e8dcddb-e22a-4006-a2b1-5556d62438c4',\n",
       "  'userData': '张铭睿'},\n",
       " {'persistedFaceId': 'af33c2c1-9467-4648-b2f3-39c65adcb7a0', 'userData': '陈婷'},\n",
       " {'persistedFaceId': '4121447a-cc8f-4815-9752-5f6ca1619339',\n",
       "  'userData': '洪可凡'},\n",
       " {'persistedFaceId': 'ade8fc2a-f92b-46bf-b411-268ebfaf8fbd',\n",
       "  'userData': '卢继志'},\n",
       " {'persistedFaceId': '7e381d2d-f937-4d44-8290-4239bad95d8f',\n",
       "  'userData': '张梓乐'},\n",
       " {'persistedFaceId': '3d27798a-218a-4358-9ad5-1704bcacef20',\n",
       "  'userData': '丘天惠'},\n",
       " {'persistedFaceId': '03bb0d32-2db1-48da-ae44-f67a94d2eb8a',\n",
       "  'userData': '林嘉茵'},\n",
       " {'persistedFaceId': 'a8461db6-0553-4674-8f8b-050db8e6dc7e',\n",
       "  'userData': '汤玲萍'},\n",
       " {'persistedFaceId': '94693276-201c-48a0-b1ac-e5825e5a5437',\n",
       "  'userData': '曾雯燕'},\n",
       " {'persistedFaceId': '6ed45750-7496-464f-ae42-c6d86e7da039',\n",
       "  'userData': '谢依希'},\n",
       " {'persistedFaceId': '7c87bd09-4afd-4914-b148-a31f15d046ea',\n",
       "  'userData': '杨悦聪'},\n",
       " {'persistedFaceId': 'd727024e-2113-426b-9800-5cb00e688e3d', 'userData': '周雨'},\n",
       " {'persistedFaceId': 'd26c6b03-2c6b-4033-8687-e8a76ea288b1',\n",
       "  'userData': '刘瑜鹏'},\n",
       " {'persistedFaceId': '289c1269-d929-4119-96d6-1d375e3a5a50',\n",
       "  'userData': '陈嘉仪'},\n",
       " {'persistedFaceId': '05373b85-bf93-4be0-b260-6dd72805e603',\n",
       "  'userData': '徐旖芊'},\n",
       " {'persistedFaceId': '0d8bca4a-d07c-48ef-9a25-9276889aff91',\n",
       "  'userData': '刘心如'},\n",
       " {'persistedFaceId': 'bd0f3d90-94d2-406c-a5bd-3e7dfd51e807', 'userData': '刘宇'},\n",
       " {'persistedFaceId': '2ba66db0-d640-4469-8e5a-bc3e29468876', 'userData': '李婷'},\n",
       " {'persistedFaceId': '161e6e22-8420-4c23-a8f4-2c2701a2b719',\n",
       "  'userData': '黄智毅'},\n",
       " {'persistedFaceId': '46b41211-1005-45ca-a646-b9f575ee5ad0',\n",
       "  'userData': '黄慧文'},\n",
       " {'persistedFaceId': 'd10257bb-5f25-40c7-b892-2bff84d7a9ce',\n",
       "  'userData': '张铭睿'},\n",
       " {'persistedFaceId': '337a29d2-3986-45b3-9e64-5537c92a85af', 'userData': '陈婷'},\n",
       " {'persistedFaceId': '8bd1c677-aa46-4500-b927-026471cdc296',\n",
       "  'userData': '洪可凡'},\n",
       " {'persistedFaceId': 'd0ca5c82-2533-40aa-bf9b-114fbbe7cc27',\n",
       "  'userData': '卢继志'},\n",
       " {'persistedFaceId': '91840fa5-1ef8-4d05-a3cc-729e3a0dd0be',\n",
       "  'userData': '张梓乐'},\n",
       " {'persistedFaceId': '46e646fb-dded-45cb-82a6-ca3b077f3bc5',\n",
       "  'userData': '黄杰琪师兄'}]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "faceId =  r_get_facelist.json()['persistedFaces']\n",
    "faceId"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0e8dcddb-e22a-4006-a2b1-5556d62438c4\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'0e8dcddb-e22a-4006-a2b1-5556d62438c4'"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for item in faceId:\n",
    "#     print(item)\n",
    "    if item['userData'] == '张铭睿':\n",
    "        print(item['persistedFaceId'])\n",
    "        delate_face = item['persistedFaceId']\n",
    "delate_face"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### delate face"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Detect face 删除列表内人脸id\n",
    "faceListId = linjm615\n",
    "delete_face_url = \"https://api-linjm.cognitiveservices.azure.com/face/v1.0/facelists/{}/persistedFaces{}\"\n",
    "assert subscription_key\n",
    "# 例如：删除黄志毅： {'persistedFaceId': '69103b48-b6c4-4f58-8ac1-4c8b84e56bc1','userData': '黄智毅'},\n",
    "\n",
    "\n",
    "persistedFaceId = '0e8dcddb-e22a-4006-a2b1-5556d62438c4'\n",
    "# 直接取上面获得的ID{'persistedFaceId': 'f18450d3-60d2-45f3-a69e-783574dc3ce8'} \n",
    "\n",
    "headers = {\n",
    "    # Request headers\n",
    "    'Content-Type': 'application/json',\n",
    "    'Ocp-Apim-Subscription-Key': subscription_key,\n",
    "}\n",
    "\n",
    "# 注意requests请求为delete\n",
    "r_delete_face = requests.delete(delete_face_url.format(faceListId,persistedFaceId),headers=headers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_delete_face"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'persistedFaces': [{'persistedFaceId': '39d84ebc-c8ea-4a0c-b714-23d7496529a9',\n",
       "   'userData': '丘天惠'},\n",
       "  {'persistedFaceId': '79d4fae2-4e19-4ff7-83fa-0b3bdeddc6de',\n",
       "   'userData': '林嘉茵'},\n",
       "  {'persistedFaceId': 'ecc62b78-a2bc-430c-8858-73c0a8af6225',\n",
       "   'userData': '汤玲萍'},\n",
       "  {'persistedFaceId': 'ea43d732-b4fb-4b63-aba4-8ac36668a90d',\n",
       "   'userData': '曾雯燕'},\n",
       "  {'persistedFaceId': '620cf149-1192-4b83-81e9-218d3b6c0d59',\n",
       "   'userData': '谢依希'},\n",
       "  {'persistedFaceId': 'f043baf1-9685-43d0-8892-af1c706daea9',\n",
       "   'userData': '杨悦聪'},\n",
       "  {'persistedFaceId': '3b612f0c-b09e-4a5b-a2dc-0e0ec9e766e3',\n",
       "   'userData': '周雨'},\n",
       "  {'persistedFaceId': 'cf94a503-2af2-4fd0-9c36-8e1c14a4d4ca',\n",
       "   'userData': '刘瑜鹏'},\n",
       "  {'persistedFaceId': '3a89cc86-4498-4f48-8fb3-159e9a703f4b',\n",
       "   'userData': '陈嘉仪'},\n",
       "  {'persistedFaceId': '2ba84b46-db53-4173-992a-6a951b9c3cbe',\n",
       "   'userData': '徐旖芊'},\n",
       "  {'persistedFaceId': 'bc8894a6-11f9-4a15-8fb4-49b2529d6ced',\n",
       "   'userData': '刘心如'},\n",
       "  {'persistedFaceId': 'f958b4ed-f2fb-452f-b96b-5a526d33cd98',\n",
       "   'userData': '刘宇'},\n",
       "  {'persistedFaceId': '84b74027-bd6b-4056-9a4b-5b32eb45301f',\n",
       "   'userData': '李婷'},\n",
       "  {'persistedFaceId': '271b2adc-23b9-4f54-a54a-0388a0da90dd',\n",
       "   'userData': '黄智毅'},\n",
       "  {'persistedFaceId': '66a5fb8b-1d80-4d85-9f4c-168858072eb2',\n",
       "   'userData': '黄慧文'},\n",
       "  {'persistedFaceId': '0e8dcddb-e22a-4006-a2b1-5556d62438c4',\n",
       "   'userData': '张铭睿'},\n",
       "  {'persistedFaceId': 'af33c2c1-9467-4648-b2f3-39c65adcb7a0',\n",
       "   'userData': '陈婷'},\n",
       "  {'persistedFaceId': '4121447a-cc8f-4815-9752-5f6ca1619339',\n",
       "   'userData': '洪可凡'},\n",
       "  {'persistedFaceId': 'ade8fc2a-f92b-46bf-b411-268ebfaf8fbd',\n",
       "   'userData': '卢继志'},\n",
       "  {'persistedFaceId': '7e381d2d-f937-4d44-8290-4239bad95d8f',\n",
       "   'userData': '张梓乐'},\n",
       "  {'persistedFaceId': '3d27798a-218a-4358-9ad5-1704bcacef20',\n",
       "   'userData': '丘天惠'},\n",
       "  {'persistedFaceId': '03bb0d32-2db1-48da-ae44-f67a94d2eb8a',\n",
       "   'userData': '林嘉茵'},\n",
       "  {'persistedFaceId': 'a8461db6-0553-4674-8f8b-050db8e6dc7e',\n",
       "   'userData': '汤玲萍'},\n",
       "  {'persistedFaceId': '94693276-201c-48a0-b1ac-e5825e5a5437',\n",
       "   'userData': '曾雯燕'},\n",
       "  {'persistedFaceId': '6ed45750-7496-464f-ae42-c6d86e7da039',\n",
       "   'userData': '谢依希'},\n",
       "  {'persistedFaceId': '7c87bd09-4afd-4914-b148-a31f15d046ea',\n",
       "   'userData': '杨悦聪'},\n",
       "  {'persistedFaceId': 'd727024e-2113-426b-9800-5cb00e688e3d',\n",
       "   'userData': '周雨'},\n",
       "  {'persistedFaceId': 'd26c6b03-2c6b-4033-8687-e8a76ea288b1',\n",
       "   'userData': '刘瑜鹏'},\n",
       "  {'persistedFaceId': '289c1269-d929-4119-96d6-1d375e3a5a50',\n",
       "   'userData': '陈嘉仪'},\n",
       "  {'persistedFaceId': '05373b85-bf93-4be0-b260-6dd72805e603',\n",
       "   'userData': '徐旖芊'},\n",
       "  {'persistedFaceId': '0d8bca4a-d07c-48ef-9a25-9276889aff91',\n",
       "   'userData': '刘心如'},\n",
       "  {'persistedFaceId': 'bd0f3d90-94d2-406c-a5bd-3e7dfd51e807',\n",
       "   'userData': '刘宇'},\n",
       "  {'persistedFaceId': '2ba66db0-d640-4469-8e5a-bc3e29468876',\n",
       "   'userData': '李婷'},\n",
       "  {'persistedFaceId': '161e6e22-8420-4c23-a8f4-2c2701a2b719',\n",
       "   'userData': '黄智毅'},\n",
       "  {'persistedFaceId': '46b41211-1005-45ca-a646-b9f575ee5ad0',\n",
       "   'userData': '黄慧文'},\n",
       "  {'persistedFaceId': 'd10257bb-5f25-40c7-b892-2bff84d7a9ce',\n",
       "   'userData': '张铭睿'},\n",
       "  {'persistedFaceId': '337a29d2-3986-45b3-9e64-5537c92a85af',\n",
       "   'userData': '陈婷'},\n",
       "  {'persistedFaceId': '8bd1c677-aa46-4500-b927-026471cdc296',\n",
       "   'userData': '洪可凡'},\n",
       "  {'persistedFaceId': 'd0ca5c82-2533-40aa-bf9b-114fbbe7cc27',\n",
       "   'userData': '卢继志'},\n",
       "  {'persistedFaceId': '91840fa5-1ef8-4d05-a3cc-729e3a0dd0be',\n",
       "   'userData': '张梓乐'},\n",
       "  {'persistedFaceId': '46e646fb-dded-45cb-82a6-ca3b077f3bc5',\n",
       "   'userData': '黄杰琪师兄'}],\n",
       " 'faceListId': 'linjm615',\n",
       " 'name': '18级网新',\n",
       " 'userData': '18级网新师兄师姐'}"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 检查你的facelist的信息\n",
    "get_facelist_url = \"https://api-linjm.cognitiveservices.azure.com/face/v1.0/facelists/linjm615\"\n",
    "r_get_facelist = requests.get(get_facelist_url,headers=headers)\n",
    "r_get_facelist.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Find similars 返回相似置信度\n",
    "- [监测人脸相似度api文档](https://docs.microsoft.com/zh-cn/rest/api/cognitiveservices/face/face/findsimilar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'faceId': '2af510e1-2758-4dba-be68-98e8947e8980',\n",
       "  'faceRectangle': {'top': 264, 'left': 207, 'width': 277, 'height': 277}}]"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Detect 检测人脸的id\n",
    "# replace <My Endpoint String> with the string from your endpoint URL\n",
    "face_api_url = 'https://api-linjm.cognitiveservices.azure.com/face/v1.0/findsimilars'\n",
    "\n",
    "# 请求正文\n",
    "image_url = 'http://huangjieqi.gitee.io/picture_storage/hjq.jpg'\n",
    "\n",
    "headers = {'Ocp-Apim-Subscription-Key': subscription_key}\n",
    "\n",
    "# 请求参数\n",
    "params = {\n",
    "    'returnFaceId': 'true',\n",
    "    'returnFaceLandmarks': 'false',\n",
    "    # 选择model\n",
    "    'recognitionModel':'recognition_03',#此参数需与facelist参数一致\n",
    "    'detectionModel':'detection_01',\n",
    "    # 可选参数,请仔细阅读API文档\n",
    "    'returnFaceAttributes': '',\n",
    "}\n",
    "\n",
    "response = requests.post(face_api_url, params=params,\n",
    "                         headers=headers, json={\"url\": image_url})\n",
    "# json.dumps 将json--->字符串\n",
    "response.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "findsimilars_url = \"https://api-linjm.cognitiveservices.azure.com/face/v1.0/findsimilars\"\n",
    "\n",
    "# 请求正文 faceId需要先检测一张照片获取\n",
    "data_findsimilars = {\n",
    "    \"faceId\":\"2af510e1-2758-4dba-be68-98e8947e8980\",#取上方的faceID\n",
    "    \"faceListId\": \"linjm1218\",\n",
    "#     \"faceIds\":faceId_02,\n",
    "    \"maxNumOfCandidatesReturned\": 10,\n",
    "    \"mode\": \"matchFace\"#matchPerson #一种为验证模式，一种为相似值模式\n",
    "    }\n",
    "\n",
    "r_findsimilars = requests.post(findsimilars_url,headers=headers,json=data_findsimilars)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_findsimilars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'persistedFaceId': '4278a690-5f78-40d7-abe5-88eab5d5494f',\n",
       "  'confidence': 0.29269},\n",
       " {'persistedFaceId': '8b1c2538-05cc-4636-8460-cfa8059d5c72',\n",
       "  'confidence': 0.20908},\n",
       " {'persistedFaceId': '5bfad450-0274-40b5-ba9f-0e4a0af9763b',\n",
       "  'confidence': 0.17849},\n",
       " {'persistedFaceId': 'c0ee4410-bca0-4a3f-acb5-74c8eb72f0a1',\n",
       "  'confidence': 0.16209},\n",
       " {'persistedFaceId': 'e61d920f-f131-464a-9a43-a82babf20358',\n",
       "  'confidence': 0.15023},\n",
       " {'persistedFaceId': '6a663a8e-725c-4c7d-bd72-5520c4a2e93e',\n",
       "  'confidence': 0.101},\n",
       " {'persistedFaceId': '8a559e64-a44b-4a4b-84dc-e14da959da3a',\n",
       "  'confidence': 0.10034},\n",
       " {'persistedFaceId': '0523267b-6750-4d1e-987d-674e0ecb0821',\n",
       "  'confidence': 0.0999},\n",
       " {'persistedFaceId': '5081698a-efe4-4be9-822c-cb58f2cc4803',\n",
       "  'confidence': 0.09955},\n",
       " {'persistedFaceId': 'd0c25191-8224-410e-9eed-df3457e0a77f',\n",
       "  'confidence': 0.09503}]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_findsimilars.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>persistedFaceId</th>\n",
       "      <th>userData</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5081698a-efe4-4be9-822c-cb58f2cc4803</td>\n",
       "      <td>丘某峰</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8cfa1b6d-b087-4cd2-be8c-55582168b497</td>\n",
       "      <td>丘天惠</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8a559e64-a44b-4a4b-84dc-e14da959da3a</td>\n",
       "      <td>林嘉茵</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7f5db725-735d-4b4f-a91b-42ac215b5aa9</td>\n",
       "      <td>汤玲萍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e386e027-8299-4703-a748-8ab7d060348c</td>\n",
       "      <td>曾雯燕</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6d3cb16e-239d-495a-a3cc-b6f346b07034</td>\n",
       "      <td>谢依希</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>81ec76dd-163f-4ee3-aa16-11a0ce73295e</td>\n",
       "      <td>杨悦聪</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>6c940c74-645a-45c8-884d-6ab34ba352c2</td>\n",
       "      <td>周雨</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>d8c64294-0629-4e81-87d5-3976ad54ac0e</td>\n",
       "      <td>刘瑜鹏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>c0ee4410-bca0-4a3f-acb5-74c8eb72f0a1</td>\n",
       "      <td>陈嘉仪</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>4278a690-5f78-40d7-abe5-88eab5d5494f</td>\n",
       "      <td>徐旖芊</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>e61d920f-f131-464a-9a43-a82babf20358</td>\n",
       "      <td>刘心如</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>a968313c-ab4e-42d0-9265-749dcf9b8529</td>\n",
       "      <td>刘宇</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>8b1c2538-05cc-4636-8460-cfa8059d5c72</td>\n",
       "      <td>李婷</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>d0c25191-8224-410e-9eed-df3457e0a77f</td>\n",
       "      <td>黄智毅</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>454e8382-9ee5-4264-b97f-02ecbe5bd987</td>\n",
       "      <td>黄慧文</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>5bfad450-0274-40b5-ba9f-0e4a0af9763b</td>\n",
       "      <td>张铭睿</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>a9c9451c-8627-4eed-b587-9410d5a61ff9</td>\n",
       "      <td>陈婷</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>6a663a8e-725c-4c7d-bd72-5520c4a2e93e</td>\n",
       "      <td>洪可凡</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>050bf519-7cdf-4b6a-8aac-52f475d282f8</td>\n",
       "      <td>卢继志</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0523267b-6750-4d1e-987d-674e0ecb0821</td>\n",
       "      <td>张梓乐</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         persistedFaceId userData\n",
       "0   5081698a-efe4-4be9-822c-cb58f2cc4803      丘某峰\n",
       "1   8cfa1b6d-b087-4cd2-be8c-55582168b497      丘天惠\n",
       "2   8a559e64-a44b-4a4b-84dc-e14da959da3a      林嘉茵\n",
       "3   7f5db725-735d-4b4f-a91b-42ac215b5aa9      汤玲萍\n",
       "4   e386e027-8299-4703-a748-8ab7d060348c      曾雯燕\n",
       "5   6d3cb16e-239d-495a-a3cc-b6f346b07034      谢依希\n",
       "6   81ec76dd-163f-4ee3-aa16-11a0ce73295e      杨悦聪\n",
       "7   6c940c74-645a-45c8-884d-6ab34ba352c2       周雨\n",
       "8   d8c64294-0629-4e81-87d5-3976ad54ac0e      刘瑜鹏\n",
       "9   c0ee4410-bca0-4a3f-acb5-74c8eb72f0a1      陈嘉仪\n",
       "10  4278a690-5f78-40d7-abe5-88eab5d5494f      徐旖芊\n",
       "11  e61d920f-f131-464a-9a43-a82babf20358      刘心如\n",
       "12  a968313c-ab4e-42d0-9265-749dcf9b8529       刘宇\n",
       "13  8b1c2538-05cc-4636-8460-cfa8059d5c72       李婷\n",
       "14  d0c25191-8224-410e-9eed-df3457e0a77f      黄智毅\n",
       "15  454e8382-9ee5-4264-b97f-02ecbe5bd987      黄慧文\n",
       "16  5bfad450-0274-40b5-ba9f-0e4a0af9763b      张铭睿\n",
       "17  a9c9451c-8627-4eed-b587-9410d5a61ff9       陈婷\n",
       "18  6a663a8e-725c-4c7d-bd72-5520c4a2e93e      洪可凡\n",
       "19  050bf519-7cdf-4b6a-8aac-52f475d282f8      卢继志\n",
       "20  0523267b-6750-4d1e-987d-674e0ecb0821      张梓乐"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "#facelist里面的数据\n",
    "faceListId_df = pd.json_normalize(r_get_facelist.json()[\"persistedFaces\"])# 升级pandas才能运行\n",
    "faceListId_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>persistedFaceId</th>\n",
       "      <th>confidence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4278a690-5f78-40d7-abe5-88eab5d5494f</td>\n",
       "      <td>0.29269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8b1c2538-05cc-4636-8460-cfa8059d5c72</td>\n",
       "      <td>0.20908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5bfad450-0274-40b5-ba9f-0e4a0af9763b</td>\n",
       "      <td>0.17849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c0ee4410-bca0-4a3f-acb5-74c8eb72f0a1</td>\n",
       "      <td>0.16209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e61d920f-f131-464a-9a43-a82babf20358</td>\n",
       "      <td>0.15023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6a663a8e-725c-4c7d-bd72-5520c4a2e93e</td>\n",
       "      <td>0.10100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8a559e64-a44b-4a4b-84dc-e14da959da3a</td>\n",
       "      <td>0.10034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0523267b-6750-4d1e-987d-674e0ecb0821</td>\n",
       "      <td>0.09990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5081698a-efe4-4be9-822c-cb58f2cc4803</td>\n",
       "      <td>0.09955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>d0c25191-8224-410e-9eed-df3457e0a77f</td>\n",
       "      <td>0.09503</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        persistedFaceId  confidence\n",
       "0  4278a690-5f78-40d7-abe5-88eab5d5494f     0.29269\n",
       "1  8b1c2538-05cc-4636-8460-cfa8059d5c72     0.20908\n",
       "2  5bfad450-0274-40b5-ba9f-0e4a0af9763b     0.17849\n",
       "3  c0ee4410-bca0-4a3f-acb5-74c8eb72f0a1     0.16209\n",
       "4  e61d920f-f131-464a-9a43-a82babf20358     0.15023\n",
       "5  6a663a8e-725c-4c7d-bd72-5520c4a2e93e     0.10100\n",
       "6  8a559e64-a44b-4a4b-84dc-e14da959da3a     0.10034\n",
       "7  0523267b-6750-4d1e-987d-674e0ecb0821     0.09990\n",
       "8  5081698a-efe4-4be9-822c-cb58f2cc4803     0.09955\n",
       "9  d0c25191-8224-410e-9eed-df3457e0a77f     0.09503"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 返回相似度的数据\n",
    "find_df = pd.json_normalize(r_findsimilars.json())# 升级pandas才能运行\n",
    "find_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>persistedFaceId</th>\n",
       "      <th>userData</th>\n",
       "      <th>confidence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4278a690-5f78-40d7-abe5-88eab5d5494f</td>\n",
       "      <td>徐旖芊</td>\n",
       "      <td>0.29269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8b1c2538-05cc-4636-8460-cfa8059d5c72</td>\n",
       "      <td>李婷</td>\n",
       "      <td>0.20908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5bfad450-0274-40b5-ba9f-0e4a0af9763b</td>\n",
       "      <td>张铭睿</td>\n",
       "      <td>0.17849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c0ee4410-bca0-4a3f-acb5-74c8eb72f0a1</td>\n",
       "      <td>陈嘉仪</td>\n",
       "      <td>0.16209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e61d920f-f131-464a-9a43-a82babf20358</td>\n",
       "      <td>刘心如</td>\n",
       "      <td>0.15023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>6a663a8e-725c-4c7d-bd72-5520c4a2e93e</td>\n",
       "      <td>洪可凡</td>\n",
       "      <td>0.10100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8a559e64-a44b-4a4b-84dc-e14da959da3a</td>\n",
       "      <td>林嘉茵</td>\n",
       "      <td>0.10034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0523267b-6750-4d1e-987d-674e0ecb0821</td>\n",
       "      <td>张梓乐</td>\n",
       "      <td>0.09990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5081698a-efe4-4be9-822c-cb58f2cc4803</td>\n",
       "      <td>丘某峰</td>\n",
       "      <td>0.09955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>d0c25191-8224-410e-9eed-df3457e0a77f</td>\n",
       "      <td>黄智毅</td>\n",
       "      <td>0.09503</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        persistedFaceId userData  confidence\n",
       "3  4278a690-5f78-40d7-abe5-88eab5d5494f      徐旖芊     0.29269\n",
       "5  8b1c2538-05cc-4636-8460-cfa8059d5c72       李婷     0.20908\n",
       "7  5bfad450-0274-40b5-ba9f-0e4a0af9763b      张铭睿     0.17849\n",
       "2  c0ee4410-bca0-4a3f-acb5-74c8eb72f0a1      陈嘉仪     0.16209\n",
       "4  e61d920f-f131-464a-9a43-a82babf20358      刘心如     0.15023\n",
       "8  6a663a8e-725c-4c7d-bd72-5520c4a2e93e      洪可凡     0.10100\n",
       "1  8a559e64-a44b-4a4b-84dc-e14da959da3a      林嘉茵     0.10034\n",
       "9  0523267b-6750-4d1e-987d-674e0ecb0821      张梓乐     0.09990\n",
       "0  5081698a-efe4-4be9-822c-cb58f2cc4803      丘某峰     0.09955\n",
       "6  d0c25191-8224-410e-9eed-df3457e0a77f      黄智毅     0.09503"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(faceListId_df, find_df,how='inner', on='persistedFaceId').sort_values(by=\"confidence\",ascending = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 设计人脸识别门禁/打卡/签到 小程序"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Face++ FaceSets 实践\n",
    "\n",
    "\n",
    ">* 1. FaceSet Create\n",
    ">* 2. FaceSet GetDetail\n",
    ">* 3. FaceSet AddFace\n",
    ">* 4. FaceSet RemoveFace\n",
    ">* 5. FaceSet Update\n",
    ">* 6. Compare Face"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 准备工作"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 先在Face++上注册一个账号，获取到api_secret和api_key\n",
    "api_secret = \"PB4-i0ErBNzG3A1J154jneohB1jpYR59\" # 复制Face++上提供的api_secret\n",
    "api_key = \"_-ycEBf_ssLXKxmzDD1mLhA-29MSbQ2f\"  # 复制Face++上提供的api_key # Replace with a valid Subscription Key here."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 面部检测 （先获取到面部识别的信息）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import requests                                                        #调用 requests\n",
    "BASE_URL = 'https://api-cn.faceplusplus.com/facepp/v3/detect'          #face++人脸识别的入口\n",
    "img_url = 'https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603541296501&di=df8f60ffc36800b54bf776fd630fe926&imgtype=0&src=http%3A%2F%2Fpics4.baidu.com%2Ffeed%2F32fa828ba61ea8d328c5b59b27bf0948271f5882.png%3Ftoken%3D853cc5bca56c55e1861e7817628d0275%26s%3D2BA36B850C1132D44DBD841D03006043'\n",
    "                                                                       #填入想要检测的图片\n",
    "headers = {\n",
    "    'Content-Type': 'application/json',\n",
    "}\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion',                  #要检测的人脸的特征\n",
    "}\n",
    "r = requests.post(BASE_URL, params=payload, headers=headers)           #发出请求\n",
    "r.status_code      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'{\"request_id\":\"1603531253,dec68b13-7a03-40e5-ae3a-96eb02a78265\",\"time_used\":205,\"faces\":[{\"face_token\":\"5d8a6a6a9333ca22be27f621fc171a51\",\"face_rectangle\":{\"top\":193,\"left\":276,\"width\":91,\"height\":91},\"attributes\":{\"gender\":{\"value\":\"Female\"},\"age\":{\"value\":32},\"smile\":{\"value\":29.564,\"threshold\":50.000},\"emotion\":{\"anger\":0.054,\"disgust\":0.054,\"fear\":5.432,\"happiness\":0.066,\"neutral\":39.574,\"sadness\":54.405,\"surprise\":0.415}}},{\"face_token\":\"1055061bf5810a80044a77b9c57ff067\",\"face_rectangle\":{\"top\":73,\"left\":47,\"width\":68,\"height\":68},\"attributes\":{\"gender\":{\"value\":\"Male\"},\"age\":{\"value\":33},\"smile\":{\"value\":99.998,\"threshold\":50.000},\"emotion\":{\"anger\":0.000,\"disgust\":0.000,\"fear\":0.000,\"happiness\":100.000,\"neutral\":0.000,\"sadness\":0.000,\"surprise\":0.000}}},{\"face_token\":\"6bf7751256417ac077292ed0ae23c9d7\",\"face_rectangle\":{\"top\":52,\"left\":520,\"width\":62,\"height\":62},\"attributes\":{\"gender\":{\"value\":\"Male\"},\"age\":{\"value\":49},\"smile\":{\"value\":100.000,\"threshold\":50.000},\"emotion\":{\"anger\":0.000,\"disgust\":0.001,\"fear\":0.000,\"happiness\":99.998,\"neutral\":0.000,\"sadness\":0.000,\"surprise\":0.000}}},{\"face_token\":\"cbe3515f69f2b9c5d1ee0a2caa1d19e5\",\"face_rectangle\":{\"top\":40,\"left\":204,\"width\":45,\"height\":45},\"attributes\":{\"gender\":{\"value\":\"Male\"},\"age\":{\"value\":30},\"smile\":{\"value\":99.989,\"threshold\":50.000},\"emotion\":{\"anger\":0.003,\"disgust\":0.024,\"fear\":0.003,\"happiness\":99.568,\"neutral\":0.026,\"sadness\":0.003,\"surprise\":0.372}}},{\"face_token\":\"785cf4025a014cf27107f5c6cced469f\",\"face_rectangle\":{\"top\":42,\"left\":402,\"width\":44,\"height\":44},\"attributes\":{\"gender\":{\"value\":\"Male\"},\"age\":{\"value\":21},\"smile\":{\"value\":0.192,\"threshold\":50.000},\"emotion\":{\"anger\":0.500,\"disgust\":0.001,\"fear\":0.001,\"happiness\":0.001,\"neutral\":99.492,\"sadness\":0.001,\"surprise\":0.005}}}],\"image_id\":\"5/FHswXoSiC+qPI1LAjB1Q==\",\"face_num\":5}\\n'"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'request_id': '1603531253,dec68b13-7a03-40e5-ae3a-96eb02a78265',\n",
       " 'time_used': 205,\n",
       " 'faces': [{'face_token': '5d8a6a6a9333ca22be27f621fc171a51',\n",
       "   'face_rectangle': {'top': 193, 'left': 276, 'width': 91, 'height': 91},\n",
       "   'attributes': {'gender': {'value': 'Female'},\n",
       "    'age': {'value': 32},\n",
       "    'smile': {'value': 29.564, 'threshold': 50.0},\n",
       "    'emotion': {'anger': 0.054,\n",
       "     'disgust': 0.054,\n",
       "     'fear': 5.432,\n",
       "     'happiness': 0.066,\n",
       "     'neutral': 39.574,\n",
       "     'sadness': 54.405,\n",
       "     'surprise': 0.415}}},\n",
       "  {'face_token': '1055061bf5810a80044a77b9c57ff067',\n",
       "   'face_rectangle': {'top': 73, 'left': 47, 'width': 68, 'height': 68},\n",
       "   'attributes': {'gender': {'value': 'Male'},\n",
       "    'age': {'value': 33},\n",
       "    'smile': {'value': 99.998, 'threshold': 50.0},\n",
       "    'emotion': {'anger': 0.0,\n",
       "     'disgust': 0.0,\n",
       "     'fear': 0.0,\n",
       "     'happiness': 100.0,\n",
       "     'neutral': 0.0,\n",
       "     'sadness': 0.0,\n",
       "     'surprise': 0.0}}},\n",
       "  {'face_token': '6bf7751256417ac077292ed0ae23c9d7',\n",
       "   'face_rectangle': {'top': 52, 'left': 520, 'width': 62, 'height': 62},\n",
       "   'attributes': {'gender': {'value': 'Male'},\n",
       "    'age': {'value': 49},\n",
       "    'smile': {'value': 100.0, 'threshold': 50.0},\n",
       "    'emotion': {'anger': 0.0,\n",
       "     'disgust': 0.001,\n",
       "     'fear': 0.0,\n",
       "     'happiness': 99.998,\n",
       "     'neutral': 0.0,\n",
       "     'sadness': 0.0,\n",
       "     'surprise': 0.0}}},\n",
       "  {'face_token': 'cbe3515f69f2b9c5d1ee0a2caa1d19e5',\n",
       "   'face_rectangle': {'top': 40, 'left': 204, 'width': 45, 'height': 45},\n",
       "   'attributes': {'gender': {'value': 'Male'},\n",
       "    'age': {'value': 30},\n",
       "    'smile': {'value': 99.989, 'threshold': 50.0},\n",
       "    'emotion': {'anger': 0.003,\n",
       "     'disgust': 0.024,\n",
       "     'fear': 0.003,\n",
       "     'happiness': 99.568,\n",
       "     'neutral': 0.026,\n",
       "     'sadness': 0.003,\n",
       "     'surprise': 0.372}}},\n",
       "  {'face_token': '785cf4025a014cf27107f5c6cced469f',\n",
       "   'face_rectangle': {'top': 42, 'left': 402, 'width': 44, 'height': 44},\n",
       "   'attributes': {'gender': {'value': 'Male'},\n",
       "    'age': {'value': 21},\n",
       "    'smile': {'value': 0.192, 'threshold': 50.0},\n",
       "    'emotion': {'anger': 0.5,\n",
       "     'disgust': 0.001,\n",
       "     'fear': 0.001,\n",
       "     'happiness': 0.001,\n",
       "     'neutral': 99.492,\n",
       "     'sadness': 0.001,\n",
       "     'surprise': 0.005}}}],\n",
       " 'image_id': '5/FHswXoSiC+qPI1LAjB1Q==',\n",
       " 'face_num': 5}"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FaceSet Create（创建人脸集合）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1. FaceSet Create\n",
    "import requests,json\n",
    "\n",
    "display_name = \"以家人之名一家人\" # 创建人脸集合的名字\n",
    "outer_id = \"family\" # 账号下全局唯一的 FaceSet 自定义标识，可以用来管理 FaceSet 对象\n",
    "user_data = \"5人，4男，1女\" # 自定义用户的信息\n",
    "\n",
    "CreateFace_Url = \"https://api-cn.faceplusplus.com/facepp/v3/faceset/create\" # 在Face++上的API文档中的FaceSet Create获取此URL\n",
    "payload = {\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'display_name':display_name,\n",
    "    'outer_id':outer_id,\n",
    "    'user_data':user_data\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(CreateFace_Url, params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'faceset_token': '08bf4610f62ac373623e6584fc44c7c6',\n",
       " 'time_used': 105,\n",
       " 'face_count': 0,\n",
       " 'face_added': 0,\n",
       " 'request_id': '1603531602,423a9aee-c78b-4b60-9271-f1501ac9350b',\n",
       " 'outer_id': 'family',\n",
       " 'failure_detail': []}"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FaceSet GetDetail（获取人脸集合信息）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "GetDetail_Url = \"https://api-cn.faceplusplus.com/facepp/v3/faceset/getdetail\" # 直接在Face++中API文档中的FaceSet GetDetail获取UPL\n",
    "\n",
    "payload = {\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'outer_id':outer_id,\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(GetDetail_Url,params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'faceset_token': '08bf4610f62ac373623e6584fc44c7c6',\n",
       " 'tags': '',\n",
       " 'time_used': 102,\n",
       " 'user_data': '5人，4男，1女',\n",
       " 'display_name': '以家人之名一家人',\n",
       " 'face_tokens': [],\n",
       " 'face_count': 0,\n",
       " 'request_id': '1603531630,9f780514-8067-4cb5-8caa-63542d8b6e95',\n",
       " 'outer_id': 'family'}"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FaceSet AddFace（增加人脸信息）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "AddFace_url = \" https://api-cn.faceplusplus.com/facepp/v3/faceset/addface\" # 直接在Face++中API文档中的FaceSet AddFace获取UPL\n",
    "\n",
    "payload = {\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'faceset_token':'08bf4610f62ac373623e6584fc44c7c6', # 选择上面创建人脸是返回的faceset_token\n",
    "    'face_tokens':'5d8a6a6a9333ca22be27f621fc171a51', # 选择上面面部检测时返回的内容的第一个face_tokens\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(AddFace_url,params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'faceset_token': '08bf4610f62ac373623e6584fc44c7c6',\n",
       " 'time_used': 552,\n",
       " 'face_count': 1,\n",
       " 'face_added': 1,\n",
       " 'request_id': '1603531796,11cfd3dd-ec4a-4ad2-903a-1cb81af0c772',\n",
       " 'outer_id': 'family',\n",
       " 'failure_detail': []}"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FaceSet RemoveFace（移除人脸信息）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "RemoveFace_url = \" https://api-cn.faceplusplus.com/facepp/v3/faceset/removeface\" # 直接在Face++中API文档中的FaceSet RemoveFace获取UPL\n",
    "\n",
    "payload = {\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'faceset_token':'08bf4610f62ac373623e6584fc44c7c6', # 选择上面创建人脸是返回的faceset_token\n",
    "    'face_tokens':'5d8a6a6a9333ca22be27f621fc171a51', # 选择上面面部检测时返回的内容的第一个face_tokens\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(RemoveFace_url,params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'faceset_token': '08bf4610f62ac373623e6584fc44c7c6',\n",
       " 'face_removed': 1,\n",
       " 'time_used': 206,\n",
       " 'face_count': 0,\n",
       " 'request_id': '1603531867,3c267b91-41df-4f96-b8c9-48bc1f04c0bb',\n",
       " 'outer_id': 'family',\n",
       " 'failure_detail': []}"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FaceSet Update（更新人脸集合信息）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "Update_url = \"https://api-cn.faceplusplus.com/facepp/v3/faceset/update\" # 直接在Face++中API文档中的FaceSet Update获取UPL\n",
    "\n",
    "payload = {\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'faceset_token':'08bf4610f62ac373623e6584fc44c7c6', # 选择上面创建人脸是返回的faceset_token\n",
    "    'user_data':\"6人，5男生，1女生\", # 在原基础上更新了一张脸，自定义的用户信息也要随之更新\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(Update_url,params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'faceset_token': '08bf4610f62ac373623e6584fc44c7c6',\n",
       " 'request_id': '1603532204,fb8c6bf0-1d07-4317-ba4a-055b0d1a2220',\n",
       " 'time_used': 88,\n",
       " 'outer_id': 'family'}"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compare Face（对比人脸相似度）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 首先填入你想要对比的人脸的照片image_url\n",
    "tansongyun = \"https://ss2.bdstatic.com/70cFvnSh_Q1YnxGkpoWK1HF6hhy/it/u=108042688,3403771306&fm=26&gp=0.jpg\"\n",
    "zhangxincheng = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603542596757&di=3f571467a03eada788e25b0e89e52458&imgtype=0&src=http%3A%2F%2Fn.sinaimg.cn%2Fsinacn10110%2F320%2Fw2048h3072%2F20191230%2F0e07-imkzenp7241222.jpg\"\n",
    "songweilong = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603542629242&di=b5723f2ada4a287bda3ded9302be8d18&imgtype=0&src=http%3A%2F%2Finews.gtimg.com%2Fnewsapp_match%2F0%2F11410505115%2F0.jpg\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 方案1:直接对比"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "Compare_url = \"https://api-cn.faceplusplus.com/facepp/v3/compare\" # 直接在Face++中API文档中获取UPL\n",
    "\n",
    "payload ={\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'image_url1':tansongyun,\n",
    "    'image_url2':zhangxincheng,\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(Compare_url,params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'faces1': [{'face_rectangle': {'width': 131,\n",
       "    'top': 105,\n",
       "    'left': 244,\n",
       "    'height': 131},\n",
       "   'face_token': '749df33f2eb88fa529a83f5d84317307'}],\n",
       " 'faces2': [{'face_rectangle': {'width': 594,\n",
       "    'top': 1291,\n",
       "    'left': 888,\n",
       "    'height': 594},\n",
       "   'face_token': 'c791a45422ea5cfee466e83b7c547901'}],\n",
       " 'time_used': 1752,\n",
       " 'thresholds': {'1e-3': 62.327, '1e-5': 73.975, '1e-4': 69.101},\n",
       " 'confidence': 37.514,\n",
       " 'image_id2': 'qPrMu+UE6QqZ4cNTngw8vw==',\n",
       " 'image_id1': 'LPGotYWPgRR7Qk0vcRo9yA==',\n",
       " 'request_id': '1603532615,81c1dcdf-6098-4147-9e65-213fcc7f54a7'}"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 方案2:与人脸集合进行对比"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 面部检测(获取face_token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "Detect_url = 'https://api-cn.faceplusplus.com/facepp/v3/detect' # 直接在Face++中API文档中获取UPL\n",
    "img_url = \"https://ss2.bdstatic.com/70cFvnSh_Q1YnxGkpoWK1HF6hhy/it/u=108042688,3403771306&fm=26&gp=0.jpg\"\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion', \n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(Detect_url,params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'request_id': '1603532754,420e35b0-02fc-4d48-987d-0f99bee28a0f',\n",
       " 'time_used': 412,\n",
       " 'faces': [{'face_token': '782ae81faf3330d1a607278d2e5b50a7',\n",
       "   'face_rectangle': {'top': 105, 'left': 244, 'width': 131, 'height': 131},\n",
       "   'attributes': {'gender': {'value': 'Female'},\n",
       "    'age': {'value': 24},\n",
       "    'smile': {'value': 100.0, 'threshold': 50.0},\n",
       "    'emotion': {'anger': 0.0,\n",
       "     'disgust': 0.0,\n",
       "     'fear': 0.02,\n",
       "     'happiness': 99.98,\n",
       "     'neutral': 0.0,\n",
       "     'sadness': 0.0,\n",
       "     'surprise': 0.0}}}],\n",
       " 'image_id': 'LPGotYWPgRR7Qk0vcRo9yA==',\n",
       " 'face_num': 1}"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 加入人脸集合"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 阿里云AI开放平台"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 人脸检测\n",
    "import requests\n",
    "import json\n",
    "\n",
    "url = \"https://dtplus-cn-shanghai.data.aliyuncs.com/face/detect?spm=a2c4g.11186623.2.10.a0597798XA2mnP\" #进入人脸检测API文档获取\n",
    "image_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603559815184&di=622042173894cfa9fc3049c3440ae04d&imgtype=0&src=http%3A%2F%2Fpics4.baidu.com%2Ffeed%2F71cf3bc79f3df8dc805fd05c2b9f538d46102835.jpeg%3Ftoken%3D954a1479957cdc765e038102092346b9%26s%3DF984DB1C17326F9044B934D9030050A2\"\n",
    "# 填入想要检测的图片URL（网上或本地都行）\n",
    "params = {\n",
    "    \"type\": \"以家人之名剧照\",\n",
    "    \"image_url\":image_url,\n",
    "    \"content\":\"以家人之名三位主角\",\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(url,params=params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 人脸识别社会/政治使用思考\n",
    "> 人脸识别的 API比较\n",
    ">> * [Face Off: Confronting Bias in Face Recognition AI](https://www.kairos.com/blog/face-off-confronting-bias-in-face-recognition-ai)\n",
    ">> * [为什么世界现在需要道德的面部识别](https://www.kairos.com/blog/why-the-world-needs-ethical-facial-recognition-now)\n",
    "    * 到2023年，全球人脸识别市场的价值估计接近100亿美元，复合年增长率为16.8％。市场背后的主要增长动力是监视市场的发展以及生物识别技术领域的政府支出。但是，面部识别的使用在其他领域也有很大贡献，例如帮助企业打击消费者欺诈，满足动态法规遵从性以及提供可获利的客户体验。\n",
    "\n",
    "-----\n",
    "> 人脸识别的偏差及API 政治经济学 \n",
    ">> * [对抗：面对面部识别AI中的偏见](https://www.kairos.com/blog/face-off-confronting-bias-in-face-recognition-ai)\n",
    "    * 发生了什么？\n",
    "        * “编码注视”或算法偏差的研究: 浅肤色男性的错误率为0.8％ ?  深色皮肤女性的错误率高达34.7％  ? (Microsoft，IBM和Face ++)\n",
    "    * 用户的反应范围从惊奇和赞美到不悦和冒犯\n",
    "        * 我们承认目前提供的种族分类（黑人，白人，亚裔，西班牙裔，其他则不足以代表丰富多样，发展迅速的文化和种族挂毯\n",
    "    * 该怎么办？\n",
    "        * 改善数据\n",
    "        * 寻求持续的反馈    \n",
    "        \n",
    ">>  * [科技行业没有应对面部识别偏见的计划](https://www.theverge.com/2018/7/26/17616290/facial-recognition-ai-bias-benchmark-test) \n",
    ">>> 公司在做什么？(一些高科技大公司支持基准和法规)     \n",
    ">>> 我们如何解决偏见问题？    \n",
    ">>> 偏差不是唯一的问题\n",
    "\n",
    ">> * [面部识别尚未准备好给执法部门使用](https://techcrunch.com/2018/06/25/facial-recognition-software-is-not-ready-for-use-by-law-enforcement/)\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 计算机视觉\n",
    "\n",
    "* 学习并完成所有Azure computer version 的API调用\n",
    "> * 分析远程图像    \n",
    "> * 分析本地图片    \n",
    "> * 生成缩略图    \n",
    "> * 提取印刷体文本和手写文本    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分析远程图像"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"categories\": [{\"name\": \"people_group\", \"score\": 0.4140625, \"detail\": {\"celebrities\": [{\"name\": \"Dilgo Khyentse Rinpoche\", \"confidence\": 0.7074617743492126, \"faceRectangle\": {\"left\": 57, \"top\": 70, \"width\": 64, \"height\": 64}}]}}, {\"name\": \"people_many\", \"score\": 0.37890625, \"detail\": {\"celebrities\": [{\"name\": \"Dilgo Khyentse Rinpoche\", \"confidence\": 0.7074617743492126, \"faceRectangle\": {\"left\": 57, \"top\": 70, \"width\": 64, \"height\": 64}}]}}], \"color\": {\"dominantColorForeground\": \"Black\", \"dominantColorBackground\": \"Black\", \"dominantColors\": [\"Black\", \"Grey\"], \"accentColor\": \"0A63C1\", \"isBwImg\": false, \"isBWImg\": false}, \"description\": {\"tags\": [\"person\", \"indoor\", \"table\", \"sitting\", \"group\", \"food\", \"people\", \"eating\", \"man\", \"woman\", \"young\", \"cake\", \"holding\", \"smiling\", \"standing\", \"restaurant\", \"birthday\", \"plate\", \"large\", \"pizza\", \"room\"], \"captions\": [{\"text\": \"Dilgo Khyentse Rinpoche et al. sitting at a table\", \"confidence\": 0.9528950758523103}]}, \"requestId\": \"47368271-e0ea-4c99-965d-98c0bdefbc3d\", \"metadata\": {\"height\": 423, \"width\": 640, \"format\": \"Jpeg\"}}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import requests\n",
    "# If you are using a Jupyter notebook, uncomment the following line.\n",
    "# %matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import json\n",
    "from PIL import Image\n",
    "from io import BytesIO\n",
    "\n",
    "# Add your Computer Vision subscription key and endpoint to your environment variables.\n",
    "# if 'COMPUTER_VISION_SUBSCRIPTION_KEY' in os.environ:\n",
    "#     subscription_key = os.environ['COMPUTER_VISION_SUBSCRIPTION_KEY']\n",
    "# else:\n",
    "#     print(\"\\nSet the COMPUTER_VISION_SUBSCRIPTION_KEY environment variable.\\n**Restart your shell or IDE for changes to take effect.**\")\n",
    "#     sys.exit()\n",
    "\n",
    "endpoint = \"https://cv-linjinmei-0615.cognitiveservices.azure.com/\" # 在Azure中创建计算机视觉资源组可获得\n",
    "# if 'COMPUTER_VISION_ENDPOINT' in os.environ:\n",
    "#     endpoint = os.environ['COMPUTER_VISION_ENDPOINT']\n",
    "subscription_key = \"004e9af2408a4d49aed6df4040c90f47\" # 创建完计算机视觉后可获取，有两个，任选其一\n",
    "\n",
    "# base url\n",
    "analyze_url = endpoint+ \"vision/v2.1/analyze\"\n",
    "\n",
    "# Set image_url to the URL of an image that you want to analyze.\n",
    "image_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603472448023&di=52e19035ab7c8780e754ca69ec72ad8d&imgtype=0&src=http%3A%2F%2Fpics4.baidu.com%2Ffeed%2F32fa828ba61ea8d328c5b59b27bf0948271f5882.png%3Ftoken%3D853cc5bca56c55e1861e7817628d0275%26s%3D2BA36B850C1132D44DBD841D03006043\"\n",
    "# 填入想要分析的图片的URL（在网上直接搜索）\n",
    "\n",
    "headers = {'Ocp-Apim-Subscription-Key': subscription_key}\n",
    "# 参数\n",
    "params = {'visualFeatures': 'Categories,Description,Color'}\n",
    "# 请求主体body\n",
    "data = {'url': image_url}\n",
    "response = requests.post(analyze_url, headers=headers,\n",
    "                         params=params, json=data)\n",
    "response.raise_for_status()\n",
    "\n",
    "# The 'analysis' object contains various fields that describe the image. The most\n",
    "# relevant caption for the image is obtained from the 'description' property.\n",
    "analysis = response.json()\n",
    "print(json.dumps(response.json()))\n",
    "image_caption = analysis[\"description\"][\"captions\"][0][\"text\"].capitalize()\n",
    "\n",
    "# Display the image and overlay it with the caption.\n",
    "image = Image.open(BytesIO(requests.get(image_url).content))\n",
    "plt.imshow(image)\n",
    "plt.axis(\"off\")\n",
    "_ = plt.title(image_caption, size=\"x-large\", y=-0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'categories': [{'name': 'people_group',\n",
       "   'score': 0.4140625,\n",
       "   'detail': {'celebrities': [{'name': 'Dilgo Khyentse Rinpoche',\n",
       "      'confidence': 0.7074617743492126,\n",
       "      'faceRectangle': {'left': 57, 'top': 70, 'width': 64, 'height': 64}}]}},\n",
       "  {'name': 'people_many',\n",
       "   'score': 0.37890625,\n",
       "   'detail': {'celebrities': [{'name': 'Dilgo Khyentse Rinpoche',\n",
       "      'confidence': 0.7074617743492126,\n",
       "      'faceRectangle': {'left': 57, 'top': 70, 'width': 64, 'height': 64}}]}}],\n",
       " 'color': {'dominantColorForeground': 'Black',\n",
       "  'dominantColorBackground': 'Black',\n",
       "  'dominantColors': ['Black', 'Grey'],\n",
       "  'accentColor': '0A63C1',\n",
       "  'isBwImg': False,\n",
       "  'isBWImg': False},\n",
       " 'description': {'tags': ['person',\n",
       "   'indoor',\n",
       "   'table',\n",
       "   'sitting',\n",
       "   'group',\n",
       "   'food',\n",
       "   'people',\n",
       "   'eating',\n",
       "   'man',\n",
       "   'woman',\n",
       "   'young',\n",
       "   'cake',\n",
       "   'holding',\n",
       "   'smiling',\n",
       "   'standing',\n",
       "   'restaurant',\n",
       "   'birthday',\n",
       "   'plate',\n",
       "   'large',\n",
       "   'pizza',\n",
       "   'room'],\n",
       "  'captions': [{'text': 'Dilgo Khyentse Rinpoche et al. sitting at a table',\n",
       "    'confidence': 0.9528950758523103}]},\n",
       " 'requestId': '47368271-e0ea-4c99-965d-98c0bdefbc3d',\n",
       " 'metadata': {'height': 423, 'width': 640, 'format': 'Jpeg'}}"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分析本地图片"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'categories': [{'name': 'people_group', 'score': 0.55078125, 'detail': {'celebrities': []}}], 'color': {'dominantColorForeground': 'Black', 'dominantColorBackground': 'Grey', 'dominantColors': ['Black', 'Grey'], 'accentColor': '475084', 'isBwImg': False, 'isBWImg': False}, 'description': {'tags': ['person', 'building', 'sitting', 'sport', 'game', 'woman', 'man', 'bench', 'young', 'cellphone', 'phone', 'people', 'holding', 'couple', 'boy', 'girl', 'group', 'talking', 'park', 'baseball', 'standing'], 'captions': [{'text': 'a man and a woman sitting on a bench', 'confidence': 0.6918608420180504}]}, 'requestId': '8b9a79ec-8e98-4608-b149-858d11f14c90', 'metadata': {'height': 538, 'width': 960, 'format': 'Jpeg'}}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "import sys\n",
    "import requests\n",
    "# If you are using a Jupyter notebook, uncomment the following line.\n",
    "# %matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from PIL import Image\n",
    "from io import BytesIO\n",
    "\n",
    "# Add your Computer Vision subscription key and endpoint to your environment variables.\n",
    "# if 'COMPUTER_VISION_SUBSCRIPTION_KEY' in os.environ:\n",
    "#     subscription_key = os.environ['COMPUTER_VISION_SUBSCRIPTION_KEY']\n",
    "# else:\n",
    "#     print(\"\\nSet the COMPUTER_VISION_SUBSCRIPTION_KEY environment variable.\\n**Restart your shell or IDE for changes to take effect.**\")\n",
    "#     sys.exit()\n",
    "\n",
    "# if 'COMPUTER_VISION_ENDPOINT' in os.environ:\n",
    "#     endpoint = os.environ['COMPUTER_VISION_ENDPOINT']\n",
    "\n",
    "# analyze_url = endpoint + \"vision/v2.1/analyze\"\n",
    "\n",
    "# Set image_path to the local path of an image that you want to analyze.\n",
    "image_path = \"D:/document/timg.jpg\" # 自己电脑上的本地连接，尽量简单点，不要太复杂\n",
    "\n",
    "# Read the image into a byte array\n",
    "image_data = open(image_path, \"rb\").read()\n",
    "headers = {'Ocp-Apim-Subscription-Key': \"004e9af2408a4d49aed6df4040c90f47\", # 在Azure上创建计算机视觉资源组获得的密钥\n",
    "           'Content-Type': 'application/octet-stream'}\n",
    "params = {'visualFeatures': 'Categories,Description,Color'}\n",
    "response = requests.post(\n",
    "    analyze_url, headers=headers, params=params, data=image_data)\n",
    "response.raise_for_status()\n",
    "\n",
    "# The 'analysis' object contains various fields that describe the image. The most\n",
    "# relevant caption for the image is obtained from the 'description' property.\n",
    "analysis = response.json()\n",
    "print(analysis)\n",
    "image_caption = analysis[\"description\"][\"captions\"][0][\"text\"].capitalize()\n",
    "\n",
    "# Display the image and overlay it with the caption.\n",
    "image = Image.open(BytesIO(image_data))\n",
    "plt.imshow(image)\n",
    "plt.axis(\"off\")\n",
    "_ = plt.title(image_caption, size=\"x-large\", y=-0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 生成缩略图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Thumbnail is 90-by-90\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "import sys\n",
    "import requests\n",
    "# If you are using a Jupyter notebook, uncomment the following line.\n",
    "# %matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from PIL import Image\n",
    "from io import BytesIO\n",
    "\n",
    "# Add your Computer Vision subscription key and endpoint to your environment variables.\n",
    "# if 'COMPUTER_VISION_SUBSCRIPTION_KEY' in os.environ:\n",
    "#     subscription_key = os.environ['COMPUTER_VISION_SUBSCRIPTION_KEY']\n",
    "# else:\n",
    "#     print(\"\\nSet the COMPUTER_VISION_SUBSCRIPTION_KEY environment variable.\\n**Restart your shell or IDE for changes to take effect.**\")\n",
    "#     sys.exit()\n",
    "\n",
    "# if 'COMPUTER_VISION_ENDPOINT' in os.environ:\n",
    "#     endpoint = os.environ['COMPUTER_VISION_ENDPOINT']\n",
    "\n",
    "thumbnail_url = \"https://cv-linjinmei-0615.cognitiveservices.azure.com/\" + \"vision/v2.1/generateThumbnail\" # 填入自己的{endpoint}\n",
    "\n",
    "# Set image_url to the URL of an image that you want to analyze.\n",
    "image_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603474405911&di=2e16b50f19143b13a7c04f6299323f91&imgtype=0&src=http%3A%2F%2Fpic1.win4000.com%2Fwallpaper%2F8%2F57c79edd0724f.jpg\"\n",
    "# 填入想要生成缩略图的图片URL\n",
    "\n",
    "headers = {'Ocp-Apim-Subscription-Key': \"dd748cf10bf9404399e5416d9399e218\"}\n",
    "params = {'width': '90', 'height': '90', 'smartCropping': 'true'} # width和height可根据自己的情况填写\n",
    "data = {'url': image_url}\n",
    "response = requests.post(thumbnail_url, headers=headers,\n",
    "                         params=params, json=data)\n",
    "response.raise_for_status()\n",
    "\n",
    "thumbnail = Image.open(BytesIO(response.content))\n",
    "\n",
    "# Display the thumbnail.\n",
    "plt.imshow(thumbnail)\n",
    "plt.axis(\"off\")\n",
    "\n",
    "# Verify the thumbnail size.\n",
    "print(\"Thumbnail is {0}-by-{1}\".format(*thumbnail.size))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 提取印刷体文本和手写文本 \n",
    "* 假如我们抓取了1000张网页，出了文本信息我们分析以外，还有每个页面的图片的信息，我们可以用提取图片文本的方式，将图片的信息也抓取下来\n",
    "* 我们进抓取了图片，想知道这些图片的内容是什么，也可以用提取文本的方式进行提取\n",
    "* ...."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "    \"status\": \"running\",\n",
      "    \"createdDateTime\": \"2020-10-24T08:20:00Z\",\n",
      "    \"lastUpdatedDateTime\": \"2020-10-24T08:20:00Z\"\n",
      "}\n",
      "{\n",
      "    \"status\": \"succeeded\",\n",
      "    \"createdDateTime\": \"2020-10-24T08:20:00Z\",\n",
      "    \"lastUpdatedDateTime\": \"2020-10-24T08:20:00Z\",\n",
      "    \"analyzeResult\": {\n",
      "        \"version\": \"3.0.0\",\n",
      "        \"readResults\": [\n",
      "            {\n",
      "                \"page\": 1,\n",
      "                \"angle\": -0.0679,\n",
      "                \"width\": 500,\n",
      "                \"height\": 321,\n",
      "                \"unit\": \"pixel\",\n",
      "                \"lines\": [\n",
      "                    {\n",
      "                        \"boundingBox\": [\n",
      "                            124,\n",
      "                            15,\n",
      "                            244,\n",
      "                            17,\n",
      "                            244,\n",
      "                            29,\n",
      "                            124,\n",
      "                            27\n",
      "                        ],\n",
      "                        \"text\": \"2011 2 393 HE\",\n",
      "                        \"words\": [\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    124,\n",
      "                                    15,\n",
      "                                    154,\n",
      "                                    16,\n",
      "                                    154,\n",
      "                                    28,\n",
      "                                    124,\n",
      "                                    27\n",
      "                                ],\n",
      "                                \"text\": \"2011\",\n",
      "                                \"confidence\": 0.749\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    180,\n",
      "                                    16,\n",
      "                                    192,\n",
      "                                    17,\n",
      "                                    191,\n",
      "                                    28,\n",
      "                                    180,\n",
      "                                    28\n",
      "                                ],\n",
      "                                \"text\": \"2\",\n",
      "                                \"confidence\": 0.405\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    210,\n",
      "                                    17,\n",
      "                                    229,\n",
      "                                    17,\n",
      "                                    228,\n",
      "                                    29,\n",
      "                                    210,\n",
      "                                    29\n",
      "                                ],\n",
      "                                \"text\": \"393\",\n",
      "                                \"confidence\": 0.856\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    231,\n",
      "                                    17,\n",
      "                                    245,\n",
      "                                    18,\n",
      "                                    245,\n",
      "                                    29,\n",
      "                                    231,\n",
      "                                    29\n",
      "                                ],\n",
      "                                \"text\": \"HE\",\n",
      "                                \"confidence\": 0.639\n",
      "                            }\n",
      "                        ]\n",
      "                    },\n",
      "                    {\n",
      "                        \"boundingBox\": [\n",
      "                            282,\n",
      "                            17,\n",
      "                            381,\n",
      "                            17,\n",
      "                            381,\n",
      "                            30,\n",
      "                            282,\n",
      "                            30\n",
      "                        ],\n",
      "                        \"text\": \"(+ 148 1 )\",\n",
      "                        \"words\": [\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    282,\n",
      "                                    17,\n",
      "                                    330,\n",
      "                                    17,\n",
      "                                    330,\n",
      "                                    30,\n",
      "                                    282,\n",
      "                                    30\n",
      "                                ],\n",
      "                                \"text\": \"(+\",\n",
      "                                \"confidence\": 0.562\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    342,\n",
      "                                    17,\n",
      "                                    365,\n",
      "                                    17,\n",
      "                                    365,\n",
      "                                    30,\n",
      "                                    342,\n",
      "                                    30\n",
      "                                ],\n",
      "                                \"text\": \"148\",\n",
      "                                \"confidence\": 0.945\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    367,\n",
      "                                    17,\n",
      "                                    372,\n",
      "                                    17,\n",
      "                                    372,\n",
      "                                    30,\n",
      "                                    367,\n",
      "                                    30\n",
      "                                ],\n",
      "                                \"text\": \"1\",\n",
      "                                \"confidence\": 0.562\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    374,\n",
      "                                    17,\n",
      "                                    381,\n",
      "                                    18,\n",
      "                                    381,\n",
      "                                    30,\n",
      "                                    374,\n",
      "                                    30\n",
      "                                ],\n",
      "                                \"text\": \")\",\n",
      "                                \"confidence\": 0.957\n",
      "                            }\n",
      "                        ]\n",
      "                    },\n",
      "                    {\n",
      "                        \"boundingBox\": [\n",
      "                            42,\n",
      "                            35,\n",
      "                            470,\n",
      "                            38,\n",
      "                            470,\n",
      "                            59,\n",
      "                            42,\n",
      "                            56\n",
      "                        ],\n",
      "                        \"text\": \"The terrible earthquake and the following tsunami\",\n",
      "                        \"words\": [\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    42,\n",
      "                                    36,\n",
      "                                    77,\n",
      "                                    36,\n",
      "                                    77,\n",
      "                                    54,\n",
      "                                    42,\n",
      "                                    52\n",
      "                                ],\n",
      "                                \"text\": \"The\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    82,\n",
      "                                    36,\n",
      "                                    147,\n",
      "                                    37,\n",
      "                                    147,\n",
      "                                    56,\n",
      "                                    82,\n",
      "                                    54\n",
      "                                ],\n",
      "                                \"text\": \"terrible\",\n",
      "                                \"confidence\": 0.982\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    150,\n",
      "                                    37,\n",
      "                                    246,\n",
      "                                    38,\n",
      "                                    246,\n",
      "                                    58,\n",
      "                                    151,\n",
      "                                    56\n",
      "                                ],\n",
      "                                \"text\": \"earthquake\",\n",
      "                                \"confidence\": 0.83\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    249,\n",
      "                                    38,\n",
      "                                    283,\n",
      "                                    38,\n",
      "                                    283,\n",
      "                                    59,\n",
      "                                    249,\n",
      "                                    59\n",
      "                                ],\n",
      "                                \"text\": \"and\",\n",
      "                                \"confidence\": 0.985\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    288,\n",
      "                                    38,\n",
      "                                    319,\n",
      "                                    38,\n",
      "                                    319,\n",
      "                                    59,\n",
      "                                    288,\n",
      "                                    59\n",
      "                                ],\n",
      "                                \"text\": \"the\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    322,\n",
      "                                    38,\n",
      "                                    399,\n",
      "                                    38,\n",
      "                                    399,\n",
      "                                    58,\n",
      "                                    322,\n",
      "                                    59\n",
      "                                ],\n",
      "                                \"text\": \"following\",\n",
      "                                \"confidence\": 0.943\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    405,\n",
      "                                    38,\n",
      "                                    471,\n",
      "                                    39,\n",
      "                                    470,\n",
      "                                    57,\n",
      "                                    404,\n",
      "                                    58\n",
      "                                ],\n",
      "                                \"text\": \"tsunami\",\n",
      "                                \"confidence\": 0.978\n",
      "                            }\n",
      "                        ]\n",
      "                    },\n",
      "                    {\n",
      "                        \"boundingBox\": [\n",
      "                            22,\n",
      "                            59,\n",
      "                            442,\n",
      "                            61,\n",
      "                            442,\n",
      "                            84,\n",
      "                            22,\n",
      "                            82\n",
      "                        ],\n",
      "                        \"text\": \"have caused so many people's injuries and deaths.\",\n",
      "                        \"words\": [\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    23,\n",
      "                                    60,\n",
      "                                    63,\n",
      "                                    61,\n",
      "                                    62,\n",
      "                                    78,\n",
      "                                    22,\n",
      "                                    76\n",
      "                                ],\n",
      "                                \"text\": \"have\",\n",
      "                                \"confidence\": 0.982\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    66,\n",
      "                                    61,\n",
      "                                    124,\n",
      "                                    62,\n",
      "                                    124,\n",
      "                                    81,\n",
      "                                    65,\n",
      "                                    79\n",
      "                                ],\n",
      "                                \"text\": \"caused\",\n",
      "                                \"confidence\": 0.978\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    129,\n",
      "                                    62,\n",
      "                                    148,\n",
      "                                    62,\n",
      "                                    148,\n",
      "                                    82,\n",
      "                                    128,\n",
      "                                    81\n",
      "                                ],\n",
      "                                \"text\": \"so\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    152,\n",
      "                                    62,\n",
      "                                    200,\n",
      "                                    63,\n",
      "                                    200,\n",
      "                                    83,\n",
      "                                    151,\n",
      "                                    82\n",
      "                                ],\n",
      "                                \"text\": \"many\",\n",
      "                                \"confidence\": 0.954\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    204,\n",
      "                                    63,\n",
      "                                    270,\n",
      "                                    63,\n",
      "                                    270,\n",
      "                                    84,\n",
      "                                    203,\n",
      "                                    83\n",
      "                                ],\n",
      "                                \"text\": \"people's\",\n",
      "                                \"confidence\": 0.975\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    276,\n",
      "                                    63,\n",
      "                                    338,\n",
      "                                    62,\n",
      "                                    338,\n",
      "                                    83,\n",
      "                                    276,\n",
      "                                    84\n",
      "                                ],\n",
      "                                \"text\": \"injuries\",\n",
      "                                \"confidence\": 0.979\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    342,\n",
      "                                    62,\n",
      "                                    379,\n",
      "                                    62,\n",
      "                                    379,\n",
      "                                    82,\n",
      "                                    342,\n",
      "                                    83\n",
      "                                ],\n",
      "                                \"text\": \"and\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    384,\n",
      "                                    62,\n",
      "                                    442,\n",
      "                                    61,\n",
      "                                    442,\n",
      "                                    80,\n",
      "                                    384,\n",
      "                                    82\n",
      "                                ],\n",
      "                                \"text\": \"deaths.\",\n",
      "                                \"confidence\": 0.956\n",
      "                            }\n",
      "                        ]\n",
      "                    },\n",
      "                    {\n",
      "                        \"boundingBox\": [\n",
      "                            20,\n",
      "                            84,\n",
      "                            482,\n",
      "                            84,\n",
      "                            482,\n",
      "                            106,\n",
      "                            20,\n",
      "                            105\n",
      "                        ],\n",
      "                        \"text\": \"Besides. many citizens become homeless. We chinese feel\",\n",
      "                        \"words\": [\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    20,\n",
      "                                    84,\n",
      "                                    82,\n",
      "                                    85,\n",
      "                                    83,\n",
      "                                    105,\n",
      "                                    21,\n",
      "                                    104\n",
      "                                ],\n",
      "                                \"text\": \"Besides.\",\n",
      "                                \"confidence\": 0.828\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    86,\n",
      "                                    85,\n",
      "                                    136,\n",
      "                                    86,\n",
      "                                    137,\n",
      "                                    106,\n",
      "                                    87,\n",
      "                                    105\n",
      "                                ],\n",
      "                                \"text\": \"many\",\n",
      "                                \"confidence\": 0.941\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    140,\n",
      "                                    86,\n",
      "                                    207,\n",
      "                                    86,\n",
      "                                    208,\n",
      "                                    107,\n",
      "                                    141,\n",
      "                                    106\n",
      "                                ],\n",
      "                                \"text\": \"citizens\",\n",
      "                                \"confidence\": 0.952\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    211,\n",
      "                                    86,\n",
      "                                    273,\n",
      "                                    86,\n",
      "                                    274,\n",
      "                                    107,\n",
      "                                    212,\n",
      "                                    107\n",
      "                                ],\n",
      "                                \"text\": \"become\",\n",
      "                                \"confidence\": 0.983\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    277,\n",
      "                                    86,\n",
      "                                    349,\n",
      "                                    86,\n",
      "                                    350,\n",
      "                                    106,\n",
      "                                    278,\n",
      "                                    107\n",
      "                                ],\n",
      "                                \"text\": \"homeless.\",\n",
      "                                \"confidence\": 0.86\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    353,\n",
      "                                    86,\n",
      "                                    383,\n",
      "                                    86,\n",
      "                                    383,\n",
      "                                    106,\n",
      "                                    354,\n",
      "                                    106\n",
      "                                ],\n",
      "                                \"text\": \"We\",\n",
      "                                \"confidence\": 0.988\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    387,\n",
      "                                    86,\n",
      "                                    445,\n",
      "                                    85,\n",
      "                                    445,\n",
      "                                    105,\n",
      "                                    387,\n",
      "                                    106\n",
      "                                ],\n",
      "                                \"text\": \"chinese\",\n",
      "                                \"confidence\": 0.983\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    448,\n",
      "                                    85,\n",
      "                                    481,\n",
      "                                    85,\n",
      "                                    481,\n",
      "                                    105,\n",
      "                                    449,\n",
      "                                    105\n",
      "                                ],\n",
      "                                \"text\": \"feel\",\n",
      "                                \"confidence\": 0.981\n",
      "                            }\n",
      "                        ]\n",
      "                    },\n",
      "                    {\n",
      "                        \"boundingBox\": [\n",
      "                            20,\n",
      "                            110,\n",
      "                            466,\n",
      "                            108,\n",
      "                            466,\n",
      "                            131,\n",
      "                            20,\n",
      "                            133\n",
      "                        ],\n",
      "                        \"text\": \"greatly sorry for the pains you are suffering. And I\",\n",
      "                        \"words\": [\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    21,\n",
      "                                    111,\n",
      "                                    77,\n",
      "                                    111,\n",
      "                                    77,\n",
      "                                    133,\n",
      "                                    21,\n",
      "                                    132\n",
      "                                ],\n",
      "                                \"text\": \"greatly\",\n",
      "                                \"confidence\": 0.978\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    81,\n",
      "                                    111,\n",
      "                                    131,\n",
      "                                    111,\n",
      "                                    131,\n",
      "                                    133,\n",
      "                                    82,\n",
      "                                    133\n",
      "                                ],\n",
      "                                \"text\": \"sorry\",\n",
      "                                \"confidence\": 0.984\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    135,\n",
      "                                    111,\n",
      "                                    166,\n",
      "                                    111,\n",
      "                                    166,\n",
      "                                    133,\n",
      "                                    135,\n",
      "                                    133\n",
      "                                ],\n",
      "                                \"text\": \"for\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    170,\n",
      "                                    111,\n",
      "                                    201,\n",
      "                                    111,\n",
      "                                    202,\n",
      "                                    133,\n",
      "                                    171,\n",
      "                                    133\n",
      "                                ],\n",
      "                                \"text\": \"the\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    205,\n",
      "                                    111,\n",
      "                                    253,\n",
      "                                    111,\n",
      "                                    254,\n",
      "                                    133,\n",
      "                                    206,\n",
      "                                    133\n",
      "                                ],\n",
      "                                \"text\": \"pains\",\n",
      "                                \"confidence\": 0.981\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    258,\n",
      "                                    111,\n",
      "                                    293,\n",
      "                                    111,\n",
      "                                    293,\n",
      "                                    132,\n",
      "                                    258,\n",
      "                                    133\n",
      "                                ],\n",
      "                                \"text\": \"you\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    297,\n",
      "                                    111,\n",
      "                                    327,\n",
      "                                    110,\n",
      "                                    327,\n",
      "                                    132,\n",
      "                                    297,\n",
      "                                    132\n",
      "                                ],\n",
      "                                \"text\": \"are\",\n",
      "                                \"confidence\": 0.986\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    331,\n",
      "                                    110,\n",
      "                                    406,\n",
      "                                    109,\n",
      "                                    406,\n",
      "                                    131,\n",
      "                                    331,\n",
      "                                    132\n",
      "                                ],\n",
      "                                \"text\": \"suffering.\",\n",
      "                                \"confidence\": 0.956\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    410,\n",
      "                                    109,\n",
      "                                    448,\n",
      "                                    109,\n",
      "                                    448,\n",
      "                                    130,\n",
      "                                    410,\n",
      "                                    131\n",
      "                                ],\n",
      "                                \"text\": \"And\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    452,\n",
      "                                    109,\n",
      "                                    466,\n",
      "                                    108,\n",
      "                                    467,\n",
      "                                    129,\n",
      "                                    452,\n",
      "                                    130\n",
      "                                ],\n",
      "                                \"text\": \"I\",\n",
      "                                \"confidence\": 0.978\n",
      "                            }\n",
      "                        ]\n",
      "                    },\n",
      "                    {\n",
      "                        \"boundingBox\": [\n",
      "                            22,\n",
      "                            135,\n",
      "                            444,\n",
      "                            135,\n",
      "                            444,\n",
      "                            155,\n",
      "                            22,\n",
      "                            156\n",
      "                        ],\n",
      "                        \"text\": \"do hope you can overcome those great difficulties.\",\n",
      "                        \"words\": [\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    22,\n",
      "                                    136,\n",
      "                                    41,\n",
      "                                    136,\n",
      "                                    41,\n",
      "                                    156,\n",
      "                                    23,\n",
      "                                    155\n",
      "                                ],\n",
      "                                \"text\": \"do\",\n",
      "                                \"confidence\": 0.982\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    45,\n",
      "                                    136,\n",
      "                                    90,\n",
      "                                    136,\n",
      "                                    90,\n",
      "                                    156,\n",
      "                                    45,\n",
      "                                    156\n",
      "                                ],\n",
      "                                \"text\": \"hope\",\n",
      "                                \"confidence\": 0.986\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    94,\n",
      "                                    136,\n",
      "                                    126,\n",
      "                                    136,\n",
      "                                    126,\n",
      "                                    156,\n",
      "                                    94,\n",
      "                                    156\n",
      "                                ],\n",
      "                                \"text\": \"you\",\n",
      "                                \"confidence\": 0.985\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    129,\n",
      "                                    136,\n",
      "                                    163,\n",
      "                                    136,\n",
      "                                    163,\n",
      "                                    156,\n",
      "                                    129,\n",
      "                                    156\n",
      "                                ],\n",
      "                                \"text\": \"can\",\n",
      "                                \"confidence\": 0.976\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    167,\n",
      "                                    136,\n",
      "                                    248,\n",
      "                                    136,\n",
      "                                    248,\n",
      "                                    156,\n",
      "                                    167,\n",
      "                                    156\n",
      "                                ],\n",
      "                                \"text\": \"overcome\",\n",
      "                                \"confidence\": 0.981\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    251,\n",
      "                                    136,\n",
      "                                    298,\n",
      "                                    136,\n",
      "                                    298,\n",
      "                                    156,\n",
      "                                    252,\n",
      "                                    156\n",
      "                                ],\n",
      "                                \"text\": \"those\",\n",
      "                                \"confidence\": 0.985\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    302,\n",
      "                                    136,\n",
      "                                    347,\n",
      "                                    136,\n",
      "                                    347,\n",
      "                                    156,\n",
      "                                    302,\n",
      "                                    156\n",
      "                                ],\n",
      "                                \"text\": \"great\",\n",
      "                                \"confidence\": 0.753\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    351,\n",
      "                                    136,\n",
      "                                    444,\n",
      "                                    135,\n",
      "                                    444,\n",
      "                                    155,\n",
      "                                    351,\n",
      "                                    156\n",
      "                                ],\n",
      "                                \"text\": \"difficulties.\",\n",
      "                                \"confidence\": 0.907\n",
      "                            }\n",
      "                        ]\n",
      "                    },\n",
      "                    {\n",
      "                        \"boundingBox\": [\n",
      "                            36,\n",
      "                            159,\n",
      "                            494,\n",
      "                            158,\n",
      "                            494,\n",
      "                            179,\n",
      "                            36,\n",
      "                            181\n",
      "                        ],\n",
      "                        \"text\": \"Please remember Japan isn't alone. People all over the\",\n",
      "                        \"words\": [\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    37,\n",
      "                                    160,\n",
      "                                    91,\n",
      "                                    160,\n",
      "                                    90,\n",
      "                                    180,\n",
      "                                    36,\n",
      "                                    179\n",
      "                                ],\n",
      "                                \"text\": \"Please\",\n",
      "                                \"confidence\": 0.981\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    95,\n",
      "                                    160,\n",
      "                                    180,\n",
      "                                    160,\n",
      "                                    179,\n",
      "                                    181,\n",
      "                                    94,\n",
      "                                    180\n",
      "                                ],\n",
      "                                \"text\": \"remember\",\n",
      "                                \"confidence\": 0.98\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    183,\n",
      "                                    160,\n",
      "                                    232,\n",
      "                                    160,\n",
      "                                    232,\n",
      "                                    181,\n",
      "                                    183,\n",
      "                                    181\n",
      "                                ],\n",
      "                                \"text\": \"Japan\",\n",
      "                                \"confidence\": 0.688\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    236,\n",
      "                                    160,\n",
      "                                    273,\n",
      "                                    160,\n",
      "                                    273,\n",
      "                                    181,\n",
      "                                    236,\n",
      "                                    181\n",
      "                                ],\n",
      "                                \"text\": \"isn't\",\n",
      "                                \"confidence\": 0.946\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    277,\n",
      "                                    160,\n",
      "                                    330,\n",
      "                                    159,\n",
      "                                    330,\n",
      "                                    181,\n",
      "                                    277,\n",
      "                                    181\n",
      "                                ],\n",
      "                                \"text\": \"alone.\",\n",
      "                                \"confidence\": 0.947\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    334,\n",
      "                                    159,\n",
      "                                    389,\n",
      "                                    159,\n",
      "                                    389,\n",
      "                                    180,\n",
      "                                    333,\n",
      "                                    180\n",
      "                                ],\n",
      "                                \"text\": \"People\",\n",
      "                                \"confidence\": 0.945\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    393,\n",
      "                                    159,\n",
      "                                    418,\n",
      "                                    159,\n",
      "                                    418,\n",
      "                                    179,\n",
      "                                    393,\n",
      "                                    180\n",
      "                                ],\n",
      "                                \"text\": \"all\",\n",
      "                                \"confidence\": 0.919\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    422,\n",
      "                                    159,\n",
      "                                    461,\n",
      "                                    159,\n",
      "                                    461,\n",
      "                                    178,\n",
      "                                    422,\n",
      "                                    179\n",
      "                                ],\n",
      "                                \"text\": \"over\",\n",
      "                                \"confidence\": 0.983\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    465,\n",
      "                                    159,\n",
      "                                    494,\n",
      "                                    159,\n",
      "                                    494,\n",
      "                                    178,\n",
      "                                    465,\n",
      "                                    178\n",
      "                                ],\n",
      "                                \"text\": \"the\",\n",
      "                                \"confidence\": 0.987\n",
      "                            }\n",
      "                        ]\n",
      "                    },\n",
      "                    {\n",
      "                        \"boundingBox\": [\n",
      "                            15,\n",
      "                            185,\n",
      "                            494,\n",
      "                            185,\n",
      "                            494,\n",
      "                            205,\n",
      "                            15,\n",
      "                            206\n",
      "                        ],\n",
      "                        \"text\": \"world are lending hands to the areas struck by tsunami\",\n",
      "                        \"words\": [\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    15,\n",
      "                                    187,\n",
      "                                    66,\n",
      "                                    186,\n",
      "                                    67,\n",
      "                                    206,\n",
      "                                    16,\n",
      "                                    206\n",
      "                                ],\n",
      "                                \"text\": \"world\",\n",
      "                                \"confidence\": 0.983\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    70,\n",
      "                                    186,\n",
      "                                    102,\n",
      "                                    186,\n",
      "                                    102,\n",
      "                                    206,\n",
      "                                    71,\n",
      "                                    206\n",
      "                                ],\n",
      "                                \"text\": \"are\",\n",
      "                                \"confidence\": 0.983\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    106,\n",
      "                                    186,\n",
      "                                    168,\n",
      "                                    186,\n",
      "                                    168,\n",
      "                                    206,\n",
      "                                    106,\n",
      "                                    206\n",
      "                                ],\n",
      "                                \"text\": \"lending\",\n",
      "                                \"confidence\": 0.924\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    172,\n",
      "                                    185,\n",
      "                                    224,\n",
      "                                    185,\n",
      "                                    224,\n",
      "                                    206,\n",
      "                                    172,\n",
      "                                    206\n",
      "                                ],\n",
      "                                \"text\": \"hands\",\n",
      "                                \"confidence\": 0.983\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    228,\n",
      "                                    185,\n",
      "                                    248,\n",
      "                                    185,\n",
      "                                    248,\n",
      "                                    206,\n",
      "                                    228,\n",
      "                                    206\n",
      "                                ],\n",
      "                                \"text\": \"to\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    252,\n",
      "                                    185,\n",
      "                                    285,\n",
      "                                    185,\n",
      "                                    285,\n",
      "                                    206,\n",
      "                                    252,\n",
      "                                    206\n",
      "                                ],\n",
      "                                \"text\": \"the\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    289,\n",
      "                                    185,\n",
      "                                    336,\n",
      "                                    185,\n",
      "                                    336,\n",
      "                                    206,\n",
      "                                    289,\n",
      "                                    206\n",
      "                                ],\n",
      "                                \"text\": \"areas\",\n",
      "                                \"confidence\": 0.955\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    339,\n",
      "                                    185,\n",
      "                                    395,\n",
      "                                    185,\n",
      "                                    396,\n",
      "                                    205,\n",
      "                                    340,\n",
      "                                    206\n",
      "                                ],\n",
      "                                \"text\": \"struck\",\n",
      "                                \"confidence\": 0.983\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    399,\n",
      "                                    185,\n",
      "                                    423,\n",
      "                                    185,\n",
      "                                    424,\n",
      "                                    205,\n",
      "                                    400,\n",
      "                                    205\n",
      "                                ],\n",
      "                                \"text\": \"by\",\n",
      "                                \"confidence\": 0.973\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    427,\n",
      "                                    185,\n",
      "                                    495,\n",
      "                                    186,\n",
      "                                    495,\n",
      "                                    204,\n",
      "                                    427,\n",
      "                                    205\n",
      "                                ],\n",
      "                                \"text\": \"tsunami\",\n",
      "                                \"confidence\": 0.98\n",
      "                            }\n",
      "                        ]\n",
      "                    },\n",
      "                    {\n",
      "                        \"boundingBox\": [\n",
      "                            16,\n",
      "                            211,\n",
      "                            472,\n",
      "                            209,\n",
      "                            472,\n",
      "                            231,\n",
      "                            16,\n",
      "                            233\n",
      "                        ],\n",
      "                        \"text\": \"and earthquake. Now that the disaster has happened.\",\n",
      "                        \"words\": [\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    16,\n",
      "                                    213,\n",
      "                                    51,\n",
      "                                    213,\n",
      "                                    51,\n",
      "                                    233,\n",
      "                                    16,\n",
      "                                    233\n",
      "                                ],\n",
      "                                \"text\": \"and\",\n",
      "                                \"confidence\": 0.983\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    55,\n",
      "                                    213,\n",
      "                                    156,\n",
      "                                    211,\n",
      "                                    155,\n",
      "                                    232,\n",
      "                                    54,\n",
      "                                    233\n",
      "                                ],\n",
      "                                \"text\": \"earthquake.\",\n",
      "                                \"confidence\": 0.902\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    159,\n",
      "                                    211,\n",
      "                                    201,\n",
      "                                    211,\n",
      "                                    201,\n",
      "                                    232,\n",
      "                                    159,\n",
      "                                    232\n",
      "                                ],\n",
      "                                \"text\": \"Now\",\n",
      "                                \"confidence\": 0.966\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    205,\n",
      "                                    211,\n",
      "                                    247,\n",
      "                                    210,\n",
      "                                    247,\n",
      "                                    231,\n",
      "                                    205,\n",
      "                                    232\n",
      "                                ],\n",
      "                                \"text\": \"that\",\n",
      "                                \"confidence\": 0.985\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    251,\n",
      "                                    210,\n",
      "                                    280,\n",
      "                                    210,\n",
      "                                    280,\n",
      "                                    231,\n",
      "                                    251,\n",
      "                                    231\n",
      "                                ],\n",
      "                                \"text\": \"the\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    284,\n",
      "                                    210,\n",
      "                                    351,\n",
      "                                    210,\n",
      "                                    351,\n",
      "                                    231,\n",
      "                                    284,\n",
      "                                    231\n",
      "                                ],\n",
      "                                \"text\": \"disaster\",\n",
      "                                \"confidence\": 0.982\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    355,\n",
      "                                    210,\n",
      "                                    388,\n",
      "                                    210,\n",
      "                                    388,\n",
      "                                    231,\n",
      "                                    355,\n",
      "                                    231\n",
      "                                ],\n",
      "                                \"text\": \"has\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    392,\n",
      "                                    210,\n",
      "                                    472,\n",
      "                                    210,\n",
      "                                    472,\n",
      "                                    232,\n",
      "                                    392,\n",
      "                                    231\n",
      "                                ],\n",
      "                                \"text\": \"happened.\",\n",
      "                                \"confidence\": 0.843\n",
      "                            }\n",
      "                        ]\n",
      "                    },\n",
      "                    {\n",
      "                        \"boundingBox\": [\n",
      "                            16,\n",
      "                            238,\n",
      "                            481,\n",
      "                            235,\n",
      "                            481,\n",
      "                            257,\n",
      "                            16,\n",
      "                            261\n",
      "                        ],\n",
      "                        \"text\": \"we should face it bravely and rebuild the homes. thus\",\n",
      "                        \"words\": [\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    16,\n",
      "                                    239,\n",
      "                                    36,\n",
      "                                    238,\n",
      "                                    36,\n",
      "                                    262,\n",
      "                                    17,\n",
      "                                    262\n",
      "                                ],\n",
      "                                \"text\": \"we\",\n",
      "                                \"confidence\": 0.983\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    41,\n",
      "                                    238,\n",
      "                                    97,\n",
      "                                    238,\n",
      "                                    97,\n",
      "                                    261,\n",
      "                                    41,\n",
      "                                    262\n",
      "                                ],\n",
      "                                \"text\": \"should\",\n",
      "                                \"confidence\": 0.985\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    101,\n",
      "                                    238,\n",
      "                                    139,\n",
      "                                    237,\n",
      "                                    140,\n",
      "                                    261,\n",
      "                                    102,\n",
      "                                    261\n",
      "                                ],\n",
      "                                \"text\": \"face\",\n",
      "                                \"confidence\": 0.983\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    144,\n",
      "                                    237,\n",
      "                                    165,\n",
      "                                    237,\n",
      "                                    165,\n",
      "                                    261,\n",
      "                                    144,\n",
      "                                    261\n",
      "                                ],\n",
      "                                \"text\": \"it\",\n",
      "                                \"confidence\": 0.988\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    170,\n",
      "                                    237,\n",
      "                                    235,\n",
      "                                    236,\n",
      "                                    235,\n",
      "                                    260,\n",
      "                                    170,\n",
      "                                    261\n",
      "                                ],\n",
      "                                \"text\": \"bravely\",\n",
      "                                \"confidence\": 0.95\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    239,\n",
      "                                    236,\n",
      "                                    274,\n",
      "                                    236,\n",
      "                                    274,\n",
      "                                    260,\n",
      "                                    240,\n",
      "                                    260\n",
      "                                ],\n",
      "                                \"text\": \"and\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    279,\n",
      "                                    236,\n",
      "                                    338,\n",
      "                                    236,\n",
      "                                    338,\n",
      "                                    259,\n",
      "                                    279,\n",
      "                                    260\n",
      "                                ],\n",
      "                                \"text\": \"rebuild\",\n",
      "                                \"confidence\": 0.983\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    342,\n",
      "                                    236,\n",
      "                                    371,\n",
      "                                    235,\n",
      "                                    372,\n",
      "                                    259,\n",
      "                                    343,\n",
      "                                    259\n",
      "                                ],\n",
      "                                \"text\": \"the\",\n",
      "                                \"confidence\": 0.983\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    376,\n",
      "                                    235,\n",
      "                                    432,\n",
      "                                    235,\n",
      "                                    432,\n",
      "                                    258,\n",
      "                                    376,\n",
      "                                    259\n",
      "                                ],\n",
      "                                \"text\": \"homes.\",\n",
      "                                \"confidence\": 0.894\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    437,\n",
      "                                    235,\n",
      "                                    480,\n",
      "                                    235,\n",
      "                                    481,\n",
      "                                    257,\n",
      "                                    437,\n",
      "                                    258\n",
      "                                ],\n",
      "                                \"text\": \"thus\",\n",
      "                                \"confidence\": 0.986\n",
      "                            }\n",
      "                        ]\n",
      "                    },\n",
      "                    {\n",
      "                        \"boundingBox\": [\n",
      "                            15,\n",
      "                            265,\n",
      "                            484,\n",
      "                            263,\n",
      "                            484,\n",
      "                            285,\n",
      "                            15,\n",
      "                            288\n",
      "                        ],\n",
      "                        \"text\": \"creating a stronger country. Tomorrow is another day.\",\n",
      "                        \"words\": [\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    15,\n",
      "                                    268,\n",
      "                                    84,\n",
      "                                    266,\n",
      "                                    85,\n",
      "                                    288,\n",
      "                                    16,\n",
      "                                    289\n",
      "                                ],\n",
      "                                \"text\": \"creating\",\n",
      "                                \"confidence\": 0.977\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    89,\n",
      "                                    266,\n",
      "                                    105,\n",
      "                                    266,\n",
      "                                    106,\n",
      "                                    287,\n",
      "                                    90,\n",
      "                                    288\n",
      "                                ],\n",
      "                                \"text\": \"a\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    109,\n",
      "                                    266,\n",
      "                                    184,\n",
      "                                    264,\n",
      "                                    185,\n",
      "                                    286,\n",
      "                                    110,\n",
      "                                    287\n",
      "                                ],\n",
      "                                \"text\": \"stronger\",\n",
      "                                \"confidence\": 0.827\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    188,\n",
      "                                    264,\n",
      "                                    262,\n",
      "                                    264,\n",
      "                                    262,\n",
      "                                    285,\n",
      "                                    189,\n",
      "                                    286\n",
      "                                ],\n",
      "                                \"text\": \"country.\",\n",
      "                                \"confidence\": 0.968\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    266,\n",
      "                                    264,\n",
      "                                    345,\n",
      "                                    263,\n",
      "                                    345,\n",
      "                                    284,\n",
      "                                    266,\n",
      "                                    285\n",
      "                                ],\n",
      "                                \"text\": \"Tomorrow\",\n",
      "                                \"confidence\": 0.914\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    349,\n",
      "                                    263,\n",
      "                                    371,\n",
      "                                    264,\n",
      "                                    371,\n",
      "                                    284,\n",
      "                                    349,\n",
      "                                    284\n",
      "                                ],\n",
      "                                \"text\": \"is\",\n",
      "                                \"confidence\": 0.984\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    376,\n",
      "                                    264,\n",
      "                                    439,\n",
      "                                    264,\n",
      "                                    439,\n",
      "                                    285,\n",
      "                                    375,\n",
      "                                    284\n",
      "                                ],\n",
      "                                \"text\": \"another\",\n",
      "                                \"confidence\": 0.83\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    443,\n",
      "                                    264,\n",
      "                                    484,\n",
      "                                    265,\n",
      "                                    483,\n",
      "                                    285,\n",
      "                                    443,\n",
      "                                    285\n",
      "                                ],\n",
      "                                \"text\": \"day.\",\n",
      "                                \"confidence\": 0.983\n",
      "                            }\n",
      "                        ]\n",
      "                    },\n",
      "                    {\n",
      "                        \"boundingBox\": [\n",
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      "                            292,\n",
      "                            258,\n",
      "                            289,\n",
      "                            258,\n",
      "                            310,\n",
      "                            15,\n",
      "                            313\n",
      "                        ],\n",
      "                        \"text\": \"All the things will be better.\",\n",
      "                        \"words\": [\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    15,\n",
      "                                    293,\n",
      "                                    43,\n",
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      "                                    43,\n",
      "                                    312,\n",
      "                                    15,\n",
      "                                    312\n",
      "                                ],\n",
      "                                \"text\": \"All\",\n",
      "                                \"confidence\": 0.986\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    47,\n",
      "                                    292,\n",
      "                                    79,\n",
      "                                    292,\n",
      "                                    79,\n",
      "                                    313,\n",
      "                                    46,\n",
      "                                    312\n",
      "                                ],\n",
      "                                \"text\": \"the\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    83,\n",
      "                                    292,\n",
      "                                    135,\n",
      "                                    291,\n",
      "                                    135,\n",
      "                                    313,\n",
      "                                    82,\n",
      "                                    313\n",
      "                                ],\n",
      "                                \"text\": \"things\",\n",
      "                                \"confidence\": 0.984\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    139,\n",
      "                                    291,\n",
      "                                    175,\n",
      "                                    291,\n",
      "                                    174,\n",
      "                                    312,\n",
      "                                    138,\n",
      "                                    313\n",
      "                                ],\n",
      "                                \"text\": \"will\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    178,\n",
      "                                    291,\n",
      "                                    203,\n",
      "                                    290,\n",
      "                                    203,\n",
      "                                    311,\n",
      "                                    178,\n",
      "                                    312\n",
      "                                ],\n",
      "                                \"text\": \"be\",\n",
      "                                \"confidence\": 0.987\n",
      "                            },\n",
      "                            {\n",
      "                                \"boundingBox\": [\n",
      "                                    207,\n",
      "                                    290,\n",
      "                                    258,\n",
      "                                    290,\n",
      "                                    258,\n",
      "                                    309,\n",
      "                                    207,\n",
      "                                    311\n",
      "                                ],\n",
      "                                \"text\": \"better.\",\n",
      "                                \"confidence\": 0.919\n",
      "                            }\n",
      "                        ]\n",
      "                    }\n",
      "                ]\n",
      "            }\n",
      "        ]\n",
      "    }\n",
      "}\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import json\n",
    "import os\n",
    "import sys\n",
    "import requests\n",
    "import time\n",
    "# If you are using a Jupyter notebook, uncomment the following line.\n",
    "# %matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import Polygon\n",
    "from PIL import Image\n",
    "from io import BytesIO\n",
    "\n",
    "missing_env = False\n",
    "# Add your Computer Vision subscription key and endpoint to your environment variables.\n",
    "# if 'COMPUTER_VISION_ENDPOINT' in os.environ:\n",
    "#   endpoint = os.environ['COMPUTER_VISION_ENDPOINT']\n",
    "# else:\n",
    "#   print(\"From Azure Cognitive Service, retrieve your endpoint and subscription key.\")\n",
    "#   print(\"\\nSet the COMPUTER_VISION_ENDPOINT environment variable, such as \\\"https://westus2.api.cognitive.microsoft.com\\\".\\n\")\n",
    "#   missing_env = True\n",
    "\n",
    "# if 'COMPUTER_VISION_SUBSCRIPTION_KEY' in os.environ:\n",
    "#    subscription_key = os.environ['COMPUTER_VISION_SUBSCRIPTION_KEY']\n",
    "# else:\n",
    "#    print(\"From Azure Cognitive Service, retrieve your endpoint and subscription key.\")\n",
    "#    print(\"\\nSet the COMPUTER_VISION_SUBSCRIPTION_KEY environment variable, such as \\\"1234567890abcdef1234567890abcdef\\\".\\n\")\n",
    "#    missing_env = True\n",
    "\n",
    "# if missing_env:\n",
    "#    print(\"**Restart your shell or IDE for changes to take effect.**\")\n",
    "#   sys.exit()\n",
    "\n",
    "text_recognition_url = \"https://cv-linjinmei-0615.cognitiveservices.azure.com/\" + \"/vision/v3.1/read/analyze\"\n",
    "\n",
    "# Set image_url to the URL of an image that you want to recognize.\n",
    "image_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603537481128&di=c428ac1dc5b8d64e344d767a062c08ea&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fimages%2F20181211%2F0b91f0137d774288a8ce6e4fc1d600b9.jpeg\"\n",
    "\n",
    "headers = {'Ocp-Apim-Subscription-Key': '004e9af2408a4d49aed6df4040c90f47'}\n",
    "data = {'url': image_url}\n",
    "response = requests.post(\n",
    "    text_recognition_url, headers=headers, json=data)\n",
    "response.raise_for_status()\n",
    "\n",
    "# Extracting text requires two API calls: One call to submit the\n",
    "# image for processing, the other to retrieve the text found in the image.\n",
    "\n",
    "# Holds the URI used to retrieve the recognized text.\n",
    "operation_url = response.headers[\"Operation-Location\"]\n",
    "\n",
    "# The recognized text isn't immediately available, so poll to wait for completion.\n",
    "analysis = {}\n",
    "poll = True\n",
    "while (poll):\n",
    "    response_final = requests.get(\n",
    "        response.headers[\"Operation-Location\"], headers=headers)\n",
    "    analysis = response_final.json()\n",
    "    \n",
    "    print(json.dumps(analysis, indent=4))\n",
    "\n",
    "    time.sleep(1)\n",
    "    if (\"analyzeResult\" in analysis):\n",
    "        poll = False\n",
    "    if (\"status\" in analysis and analysis['status'] == 'failed'):\n",
    "        poll = False\n",
    "\n",
    "polygons = []\n",
    "if (\"analyzeResult\" in analysis):\n",
    "    # Extract the recognized text, with bounding boxes.\n",
    "    polygons = [(line[\"boundingBox\"], line[\"text\"])\n",
    "                for line in analysis[\"analyzeResult\"][\"readResults\"][0][\"lines\"]]\n",
    "\n",
    "# Display the image and overlay it with the extracted text.\n",
    "image = Image.open(BytesIO(requests.get(image_url).content))\n",
    "ax = plt.imshow(image)\n",
    "for polygon in polygons:\n",
    "    vertices = [(polygon[0][i], polygon[0][i+1])\n",
    "                for i in range(0, len(polygon[0]), 2)]\n",
    "    text = polygon[1]\n",
    "    patch = Polygon(vertices, closed=True, fill=False, linewidth=2, color='y')\n",
    "    ax.axes.add_patch(patch)\n",
    "    plt.text(vertices[0][0], vertices[0][1], text, fontsize=20, va=\"top\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 学习人脸识别和计算机视觉心得体会\n",
    "\n",
    "> 历程艰辛！    \n",
    "> 不会放弃！    \n",
    "> 终得成果！    \n",
    "> 分享经验吧～"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "刚开始提到这一课程名称时，API、机器学习与人工智能，感觉好高大上啊。但是接触了才发现原来它这么难学，学起来这么吃力，慢慢地就对这一课程失去了兴趣，看到代码就头晕，面对代码无从下手，真的太痛苦，最难受的是明明写的和老师讲的一模一样，但返回的结果是404时，感觉头都要大了。这两周老师讲的详细了点，慢慢可以跟上老师的节奏了，写的代码也可以运行成功，这对来说是很大的鼓励，终于不再是404，这种感觉真得太棒了。而且，慢慢地自己也可以通过阅读相关的API文档来写代码，从阅读API文档和错误的代码返回的信息，一步步积累一些经验，避免下次再犯同样的错误，也学会通过和同学交流，在不同的错误中寻找解决方法，查询相关的内容。对我来说，要学好这一门课程，真得要下很大的功夫，也会在此过程中遭受到很多的困难，但我希望自己可以认真学习，不放弃，希望结果不会让我失望吧！"
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